Awesome-FL

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Awesome-FL 是一个专注于联邦学习（Federated Learning）领域的开源资源聚合平台，旨在为学术界和工业界提供全面、及时的学术信息。它系统地整理了该领域的高质量论文、主流开发框架、基准数据集、教程课程以及相关的研讨会资讯，并按人工智能、机器学习、安全隐私、计算机视觉、自然语言处理等细分方向进行了详细分类。

在联邦学习研究快速迭代的背景下，研究人员往往面临文献分散、资源查找困难的问题。Awesome-FL 通过结构化的知识库，帮助用户高效定位顶会顶刊论文与实用代码工具，极大地降低了入门门槛和调研成本。其独特亮点在于不仅涵盖通用联邦学习资源，还深入梳理了图数据、表格数据等特定场景下的前沿进展，并曾利用自动化项目追踪论文更新动态。

该资源主要适合从事联邦学习算法研究的高校科研人员、研究生，以及需要落地隐私计算技术的开发者使用。无论是希望快速了解领域全貌的初学者，还是寻求最新技术突破的资深专家，都能从中获得宝贵参考。需要注意的是，随着核心维护者完成博士学业并调整研究重心，目前的更新频率已调整为月度或季度，部分深度维护内容有所精简，但其积累的海量历史资源依然具有极高的查阅价值。

使用场景

某医疗 AI 初创团队正研发跨医院联合诊断模型，需在严格保护患者隐私的前提下，快速调研联邦学习在医学影像领域的最新算法与开源框架。

没有 Awesome-FL 时

  • 文献检索如大海捞针：研究人员需在 IEEE、CVPR 等多个顶级会议网站手动筛选，难以区分哪些论文真正涉及“联邦学习 + 医疗影像”，耗时数周仍可能遗漏关键成果。
  • 技术选型缺乏对比依据：面对分散在各处的开源框架，团队无法快速评估哪个支持异构数据或具备差分隐私功能，导致原型开发阶段反复试错。
  • 数据与教程零散难寻：适合联邦学习的医疗数据集隐藏在不同机构的个人页中，且缺乏配套的复现教程，新人上手门槛极高。
  • 前沿动态滞后：由于缺乏统一的追踪机制，团队往往在项目中期才发现已有更优的聚合算法发表，导致技术路线被迫重构。

使用 Awesome-FL 后

  • 精准定位顶会成果：直接通过"CV"和"FL in top-tier conference"分类，一键获取近年所有关于联邦学习在计算机视觉（含医学影像）的核心论文，调研效率提升十倍。
  • 框架决策有的放矢：利用"Framework"板块中按功能分类的列表，迅速锁定支持非独立同分布（Non-IID）数据的成熟框架，大幅缩短技术验证周期。
  • 资源一站式获取：从"Datasets"和"Tutorials"栏目直接下载经过清洗的基准数据集及配套代码，团队成员当天即可跑通基线模型。
  • 紧跟学术脉搏：借助其自动追踪机制和定期更新的日志，实时掌握最新的研讨会（Workshops）和特刊信息，确保技术方案始终处于行业前沿。

Awesome-FL 将原本碎片化的学术资源整合为结构化知识图谱，让研发团队从繁琐的信息搜集者转变为专注技术创新的实践者。

运行环境要求

GPU

未说明

内存

未说明

依赖
notesAwesome-FL 是一个联邦学习（Federated Learning）领域的资源列表（Awesome List），主要收录论文、框架、数据集、综述和教程等链接，本身不是一个可执行的软件工具或代码库，因此没有具体的操作系统、GPU、内存、Python 版本或依赖库的安装需求。用户需根据列表中引用的具体框架或论文代码去查看相应的环境要求。
python未说明
Awesome-FL hero image

快速开始

联邦学习资源

星标 Awesome 许可证

目录

我们使用另一个项目来自动跟踪联邦学习论文的更新，如果您需要，请点击 FL-paper-update-tracker。

请注意，如果此页面未显示全部内容，请 访问官方主页以获取完整信息。

将会有更多条目被添加到仓库中。请随时通过提交 issue 报告、提交 pull request 或发送电子邮件至 (im.young@foxmail.com) 建议其他关键资源。如果您想与更多联邦学习领域的同行交流，请加入 QQ 群 [联邦学习交流群]，群号为 833638275。祝您阅读愉快！

仓库更新通知

2024年9月30日

尊敬的用户们，我们在此告知您一些将影响本开源仓库的变化。仓库的所有者兼主要贡献者 @youngfish42 已于2024年9月30日顺利完成博士学业 🎓，此后已调整其研究方向。这一变化将影响仓库论文列表的更新频率和深度。

相较于以往的定期更新，我们预计今后论文列表将改为每月或每季度更新一次。此外，更新的内容也将有所减少。例如，关于作者所在机构及开源代码的相关信息将不再持续维护。

我们理解这可能会对您从本仓库中获得的价值产生一定影响。因此，我们诚挚地邀请更多贡献者参与内容的更新工作。通过大家的共同努力，我们将确保该仓库继续成为一项宝贵的资源。

感谢您的理解，并期待您一如既往的支持与贡献。

此致敬礼，

白小鱼 (youngfish)

论文

分类

  • 人工智能（IJCAI、AAAI、AISTATS、ALT、AI）

  • 机器学习（NeurIPS、ICML、ICLR、COLT、UAI、Machine Learning、JMLR、TPAMI）

  • 数据挖掘（KDD、WSDM）

  • 安全（S&P、CCS、USENIX Security、NDSS）

  • 计算机视觉（ICCV、CVPR、ECCV、MM、IJCV）

  • 自然语言处理（ACL、EMNLP、NAACL、COLING）

  • 信息检索（SIGIR）

  • 数据库（SIGMOD、ICDE、VLDB）

  • 网络（SIGCOMM、INFOCOM、MOBICOM、NSDI、WWW）

  • 系统（OSDI、SOSP、ISCA、MLSys、EuroSys、TPDS、DAC、TOCS、TOS、TCAD、TC）

  • 其他（ICSE、FOCS、STOC）

活动
场所 2024-2020 2020年之前
IJCAI 25, 24, 23, 22, 21, 20 19
AAAI 25, 24, 23, 22, 21, 20 -
AISTATS 25, 24, 23, 22, 21, 20 -
ALT 22 -
AI (J) 25, 23 -
NeurIPS 24, 23, 22, 21, 20 18, 17
ICML 25, 24, 23, 22, 21, 20 19
ICLR 25, 24, 23, 22, 21, 20 -
COLT 23 -
UAI 25, 24, 23, 22, 21 -
Machine Learning (J) 25, 24, 23, 22 -
JMLR (J) 24, 23, 22 -
TPAMI (J) 25, 24, 23, 22 -
KDD 25, 24, 23, 22, 21, 20
WSDM 25, 24, 23, 22, 21 19
S&P 25, 24, 23, 22 19
CCS 24, 23, 22, 21, 19 17
USENIX Security 23, 22, 20 -
NDSS 25, 24, 23, 22, 21 -
CVPR 25, 24, 23, 22, 21 -
ICCV 23,21 -
ECCV 24, 22, 20 -
MM 24, 23, 22, 21, 20 -
IJCV (J) 25, 24 -
ACL 25, 24, 23, 22, 21 19
NAACL 24, 22, 21 -
EMNLP 24, 23, 22, 21, 20 -
COLING 25, 20 -
SIGIR 25, 24, 23, 22, 21, 20 -
SIGMOD 22, 21 -
ICDE 25, 24, 23, 22, 21 -
VLDB 25, 24, 23, 22, 21, 21, 20 -
SIGCOMM 25 -
INFOCOM 25, 24, 23, 22, 21, 20 19, 18
MobiCom 24, 23, 22, 21, 20
NSDI 25, 23(1, 2) -
WWW 25, 24, 23, 22, 21
OSDI 21 -
SOSP 21 -
ISCA 24 -
MLSys 24, 23, 22, 20 19
EuroSys 25, 24, 23, 22, 21, 20
TPDS (J) 25, 24, 23, 22, 21, 20 -
DAC 25, 24, 22, 21 -
TOCS - -
TOS - -
TCAD 25, 24, 23, 22, 21 -
TC 25, 24, 23, 22, 21 -
ICSE 25, 23, 21 -
FOCS - -
STOC - -

关键词

统计：:fire: 代码可获取且星标 >= 100 | :star: 引用次数 >= 50 | :mortar_board: 顶级期刊

kg.: 知识图谱 | data.: 数据集  |   surv.: 调查

联邦学习在顶级期刊中的发表情况

Nature（及其子刊）、Cell、Science（及其子刊）和 PNAS 中关于联邦学习的论文，可通过 WOS 检索引擎查询。

联邦学习在顶级期刊中的发表情况
标题 所属机构 发表期刊 年份 资料
基于全同态加密的计算高效拜占庭鲁棒联邦学习 Nat. Mach. Intell. 2025 [出版物] [PDF] [代码]
激励模型共享市场中的包容性贡献 Nat. Commun. 2025 [出版物] [代码]
FedECA：用于分布式环境中生存时间数据因果推断的联邦外部对照臂 Nat. Commun. 2025 [出版物] [代码]
使用FedProt进行隐私保护的多中心差异蛋白质丰度分析 Nat. Comput. Sci. 2025 [出版物] [代码]
通过联邦肿瘤分割挑战实现医疗AI算法的公平去中心化基准测试 Nat. Commun. 2025 [出版物] [代码]
一种应用于胸部X光的完全开放的AI基础模型 Nature 2025 [出版物] [代码]
利用具有原位物理不可克隆函数和真随机数发生器的忆阻器存内计算芯片进行联邦学习 Nat. Electron. 2025 [出版物]
基于联邦元学习重构个性化物联网的框架 中山大学 Nat. Commun. 2025 [出版物] [代码]
在联邦医学影像中实现灵活的公平性度量 香港中文大学 Nat. Commun. 2025 [出版物] [代码]
向面向公平且隐私保护的医疗增强协作学习迈进 哈尔滨工业大学 Nat. Commun. 2025 [出版物] [代码]
基于知识蒸馏的药物发现中的数据驱动联邦学习 Lhasa Limited Nat. Mach. Intell. 2025 [出版物] [代码]
用于公平联邦模型的分布式交叉学习——基于加州五家医院数据的隐私保护预测 耶鲁大学；UCSD Nat. Commun. 2025 [出版物]
用于同时保护私有数据和深度学习模型的物理不可克隆存内计算 北京大学 Nat. Commun. 2025 [出版物] [新闻]
MatSwarm：可信蜂群迁移学习驱动的材料计算，用于安全的大数据共享 USTB；NTU Nat. Commun. 2024 [出版物] [代码]
通过联邦分割学习将边缘智能引入智能电表 香港大学 Nat. Commun. 2024 [出版物] [新闻]
一项国际研究展示了一种用于儿童脑肿瘤的联邦学习AI平台 斯坦福大学 Nat. Commun. 2024 [出版物] [代码]
PPML-Omics：一种保护患者隐私的联邦机器学习方法，适用于组学数据 KAUST Science Advances 2024 [出版物] [代码]
神经网络伦理问题并非联邦学习所能解决 TUM；UvA Nat. Mach. Intell.(评论) 2024 [出版物]
用于识别胃癌术后高风险复发患者的鲁棒联邦学习模型 江门市中心医院；桂林航天工业学院；桂林电子科技大学； Nat. Commun. 2024 [出版物] [代码]
无需优秀教师的隐私保护联邦蒸馏中的选择性知识共享 香港科技大学 Nat. Commun. 2024 [出版物] [PDF] [代码]
欧洲精准肿瘤学的联邦学习系统：DigiONE IQVIA Cancer Research BV Nat. Med. (评论) 2024 [出版物]
基于Qline架构的多客户端分布式盲量子计算 罗马萨皮恩扎大学 Nat. Commun. 2023 [出版物] [PDF]
设备无关的量子随机性增强零知识证明 中国科学技术大学 PNAS 2023 [出版物] [PDF] [新闻]
通过联邦机器学习实现盈利性直接回收的协作式、隐私保护退役电池分类 清华大学 Nat. Commun. 2023 [出版物]
倡导神经数据隐私与神经技术监管 哥伦比亚大学 Nat. Protoc. (观点) 2023 [出版物]
通过MedPerf进行医疗人工智能的联邦基准测试 IHU斯特拉斯堡；斯特拉斯堡大学；达纳-法伯癌症研究所；威尔康奈尔医学院；哈佛T.H.陈公共卫生学院；MIT；英特尔 Nat. Mach. Intell. 2023 [出版物] [PDF] [代码]
医疗与健康领域的人工智能算法公平性 哈佛医学院；哈佛-麻省理工学院布罗德研究所；达纳-法伯癌症研究所 Nat. Biomed. Eng. (观点) 2023 [出版物] [PDF]
用于联邦学习的差分隐私知识转移 清华大学 Nat. Commun. 2023 [出版物] [代码]
通过代理模型共享实现去中心化联邦学习 Layer 6 AI；滑铁卢大学；Vector Institute Nat. Commun. 2023 [出版物] [PDF] [代码]
符合数据保护法规的研究中的联邦机器学习 汉堡大学 Nat. Mach. Intell.(评论) 2023 [出版物]
用于预测三阴性乳腺癌新辅助化疗组织学反应的联邦学习 Owkin Nat. Med. 2023 [出版物] [代码]
稀有癌症边界检测中的联邦学习助力大数据应用 宾夕法尼亚大学 Nat. Commun. 2022 [出版物] [PDF] [代码]
神经网络伦理问题并非联邦学习所能解决 Hugging Face Nat. Mach. Intell. (评论) 2022 [出版物]
用于无监督脑部异常检测的联邦解耦表示学习 TUM Nat. Mach. Intell. 2022 [出版物] [PDF] [代码]
将医疗领域的机器学习从开发转向部署，从模型转向数据 斯坦福大学；Greenstone Biosciences Nat. Biomed. Eng. (综述文章) 2022 [出版物]
一种用于隐私保护个性化的联邦图神经网络框架 清华大学 Nat. Commun. 2022 [出版物] [代码] [解读]
基于知识蒸馏的通信效率型联邦学习 清华大学 Nat. Commun. 2022 [出版物] [PDF] [代码]
引领无线边缘人工智能的联邦神经形态学习 厦门大学；NTU Nat. Commun. 2022 [出版物] [代码] [解读]
一种新颖的去中心化联邦学习方法，可用于在全球范围内分布、质量较差且受隐私保护的医疗数据上训练 伍伦贡大学 Sci. Rep. 2022 [出版物]
通过人工智能中的隐私保护协作推进COVID-19诊断 华中科技大学 Nat. Mach. Intell. 2021 [出版物] [PDF] [代码]
用于预测COVID-19患者临床结局的联邦学习 MGH放射科和哈佛医学院 Nat. Med. 2021 [出版物] [代码]
隐私保护协作式机器学习中的对抗干扰及其缓解措施 伦敦帝国理工学院；TUM；OpenMined Nat. Mach. Intell.(观点) 2021 [出版物]
分散式且保密的临床机器学习：蜂群学习 :star: DZNE；波恩大学； Nature :mortar_board: 2021 [出版物] [代码] [软件] [解读]
多机构医学影像上的端到端隐私保护深度学习 TUM；伦敦帝国理工学院；OpenMined Nat. Mach. Intell. 2021 [出版物] [代码] [解读]
通信效率型联邦学习 香港中文大学；普林斯顿大学 PANS. 2021 [出版物] [代码]
利用合成X光片打破医疗数据共享壁垒 亚琛工业大学 Science. Advances. 2020 [出版物] [代码]
医疗影像中的安全、隐私保护且联邦的机器学习 :star: TUM；伦敦帝国理工学院；OpenMined Nat. Mach. Intell.(观点) 2020 [出版物]

联邦学习在顶级人工智能会议和期刊中

联邦学习相关论文被顶级人工智能（Artificial Intelligence）会议和期刊接收，包括 IJCAI（国际人工智能联合会议）、AAAI（AAAI 人工智能会议）、AISTATS（人工智能与统计学会议）、ALT（国际算法学习理论会议）、AI（人工智能期刊）。

联邦学习在顶级人工智能会议和期刊中
Title Affiliation Venue Year Materials
Exploiting Label Skewness for Spiking Neural Networks in Federated Learning IJCAI 2025 [PUB]
FedHAN: A Cache-Based Semi-Asynchronous Federated Learning Framework Defending Against Poisoning Attacks in Heterogeneous Clients IJCAI 2025 [PUB]
Heterogeneous Federated Learning with Scalable Server Mixture-of-Experts IJCAI 2025 [PUB]
Pixel-wise Divide and Conquer for Federated Vessel Segmentation IJCAI 2025 [PUB]
Universal Backdoor Defense via Label Consistency in Vertical Federated Learning IJCAI 2025 [PUB]
Where Does This Data Come From? Enhanced Source Inference Attacks in Federated Learning IJCAI 2025 [PUB]
Optimizing Personalized Federated Learning Through Adaptive Layer-Wise Learning IJCAI 2025 [PUB] [COCE]
FedDLAD: A Federated Learning Dual-Layer Anomaly Detection Framework for Enhancing Resilience Against Backdoor Attacks IJCAI 2025 [PUB] [CODE]
Federated Multi-view Graph Clustering with Incomplete Attribute Imputation IJCAI 2025 [PUB]
ADPFedGNN: Adaptive Decoupling Personalized Federated Graph Neural Network IJCAI 2025 [PUB]
Approximated Behavioral Metric-based State Projection for Federated Reinforcement Learning IJCAI 2025 [PUB]
FissionVAE: Federated Non-IID Image Generation with Latent Space and Decoder Decomposition IJCAI 2025 [PUB]
FedBG: Proactively Mitigating Bias in Cross-Domain Graph Federated Learning Using Background Data IJCAI 2025 [PUB]
FedCCH: Automatic Personalized Graph Federated Learning for Inter-Client and Intra-Client Heterogeneity IJCAI 2025 [PUB]
FedCPD:Personalized Federated Learning with Prototype-Enhanced Representation and Memory Distillation IJCAI 2025 [PUB]
Data Poisoning Attack Defense and Evolutionary Domain Adaptation for Federated Medical Image Segmentation IJCAI 2025 [PUB]
Distilling A Universal Expert from Clustered Federated Learning IJCAI 2025 [PUB]
CSAHFL:Clustered Semi-Asynchronous Hierarchical Federated Learning for Dual-layer Non-IID in Heterogeneous Edge Computing Networks IJCAI 2025 [PUB]
FAST: A Lightweight Mechanism Unleashing Arbitrary Client Participation in Federated Learning IJCAI 2025 [PUB]
Hypernetwork Aggregation for Decentralized Personalized Federated Learning IJCAI 2025 [PUB]
Federated Domain Generalization with Decision Insight Matrix IJCAI 2025 [PUB]
Generic Adversarial Attack Framework Against Vertical Federated Learning IJCAI 2025 [PUB]
One-shot Federated Learning Methods: A Practical Guide IJCAI 2025 [PUB]
Federated Learning at the Forefront of Fairness: A Multifaceted Perspective IJCAI 2025 [PUB]
Performance Guaranteed Poisoning Attacks in Federated Learning: A Sliding Mode Approach IJCAI 2025 [PUB]
Federated Deconfounding and Debiasing Learning for Out-of-Distribution Generalization IJCAI 2025 [PUB]
FedAPA: Server-side Gradient-Based Adaptive Personalized Aggregation for Federated Learning on Heterogeneous Data IJCAI 2025 [PUB] [CODE]
An Empirical Study of Federated Prompt Learning for Vision Language Model IJCAI 2025 [PUB]
FedCM: Client Clustering and Migration in Federated Learning via Gradient Path Similarity and Update Direction Deviation IJCAI 2025 [PUB]
Zero-shot Federated Unlearning via Transforming from Data-Dependent to Personalized Model-Centric IJCAI 2025 [PUB]
DaringFed: A Dynamic Bayesian Persuasion Pricing for Online Federated Learning Under Two-sided Incomplete Information IJCAI 2025 [PUB]
Backdoor Attack on Vertical Federated Graph Neural Network Learning IJCAI 2025 [PUB]
Federated Low-Rank Adaptation for Foundation Models: A Survey IJCAI 2025 [PUB]
Learning Heterogeneous Performance-Fairness Trade-offs in Federated Learning IJCAI 2025 [PUB]
FedSaaS: Class-Consistency Federated Semantic Segmentation via Global Prototype Supervision and Local Adversarial Harmonization IJCAI 2025 [PUB]
A Multi-Granularity Clustering Approach for Federated Backdoor Defense with the Adam Optimizer IJCAI 2025 [PUB]
Federated Stochastic Bilevel Optimization with Fully First-Order Gradients IJCAI 2025 [PUB]
AdaptPFL: Unlocking Cross-Device Palmprint Recognition via Adaptive Personalized Federated Learning with Feature Decoupling IJCAI 2025 [PUB]
Rethinking Federated Graph Learning: A Data Condensation Perspective IJCAI 2025 [PUB]
MMGIA: Gradient Inversion Attack Against Multimodal Federated Learning via Intermodal Correlation IJCAI 2025 [PUB]
Enhancing the Performance of Global Model by Improving the Adaptability of Local Models in Federated Learning IJCAI 2025 [PUB]
Finite-Time Analysis of Heterogeneous Federated Temporal Difference Learning IJCAI 2025 [PUB]
Inconsistency-Based Federated Active Learning IJCAI 2025 [PUB]
Optimising Clinical Federated Learning through Mode Connectivity-based Model Aggregation AISTATS 2025 [PUB] [CODE]
FedBaF: Federated Learning Aggregation Biased by a Foundation Model AISTATS 2025 [PUB]
Global Group Fairness in Federated Learning via Function Tracking AISTATS 2025 [PUB] [CODE]
On the Power of Adaptive Weighted Aggregation in Heterogeneous Federated Learning and Beyond AISTATS 2025 [PUB] [CODE]
Federated UCBVI: Communication-Efficient Federated Regret Minimization with Heterogeneous Agents AISTATS 2025 [PUB] [CODE]
ADEPT: Hierarchical Bayes Approach to Personalized Federated Unsupervised Learning AISTATS 2025 [PUB] [CODE]
Federated Causal Inference: Multi-Study ATE Estimation beyond Meta-Analysis AISTATS 2025 [PUB] [CODE]
The cost of local and global fairness in Federated Learning AISTATS 2025 [PUB] [CODE]
Federated Communication-Efficient Multi-Objective Optimization AISTATS 2025 [PUB] [CODE]
Refined Analysis of Constant Step Size Federated Averaging and Federated Richardson-Romberg Extrapolation AISTATS 2025 [PUB] [CODE]
Personalizing Low-Rank Bayesian Neural Networks Via Federated Learning AISTATS 2025 [PUB] [CODE]
On the Convergence of Continual Federated Learning Using Incrementally Aggregated Gradients AISTATS 2025 [PUB] [CODE]
DPFL: Decentralized Personalized Federated Learning AISTATS 2025 [PUB] [CODE]
FedHM: Efficient federated learning for heterogeneous models via low-rank factorization AI 2025 [PUB]
Learning Together Securely: Prototype-Based Federated Multi-Modal Hashing for Safe and Efficient Multi-Modal Retrieval AAAI 2025 [PUB]
Single-Loop Federated Actor-Critic across Heterogeneous Environments AAAI 2025 [PUB]
Improving Federated Domain Generalization Through Dynamical Weights Calculated from Data Influences on Global Model Update AAAI 2025 [PUB]
FedSA: A Unified Representation Learning via Semantic Anchors for Prototype-based Federated Learning AAAI 2025 [PUB]
FedGOG: Federated Graph Out-of-Distribution Generalization with Diffusion Data Exploration and Latent Embedding Decorrelation AAAI 2025 [PUB]
ConFREE: Conflict-free Client Update Aggregation for Personalized Federated Learning AAAI 2025 [PUB]
Personalized Label Inference Attack in Federated Transfer Learning via Contrastive Meta Learning AAAI 2025 [PUB]
Rethinking Byzantine Robustness in Federated Recommendation from Sparse Aggregation Perspective AAAI 2025 [PUB]
Asynchronous Federated Clustering with Unknown Number of Clusters AAAI 2025 [PUB]
Generating Synthetic Data for Unsupervised Federated Learning of Cross-Modal Retrieval AAAI 2025 [PUB]
HaCore: Efficient Coreset Construction with Locality Sensitive Hashing for Vertical Federated Learning AAAI 2025 [PUB]
LoGoFair: Post-Processing for Local and Global Fairness in Federated Learning AAAI 2025 [PUB]
Multifaceted User Modeling in Recommendation: A Federated Foundation Models Approach AAAI 2025 [PUB]
Modeling Inter-Intra Heterogeneity for Graph Federated Learning AAAI 2025 [PUB]
pFedES: Generalized Proxy Feature Extractor Sharing for Model Heterogeneous Personalized Federated Learning AAAI 2025 [PUB]
First-Order Federated Bilevel Learning AAAI 2025 [PUB]
GAS: Generative Activation-Aided Asynchronous Split Federated Learning AAAI 2025 [PUB]
FedVCK: Non-IID Robust and Communication-Efficient Federated Learning via Valuable Condensed Knowledge for Medical Image Analysis AAAI 2025 [PUB]
Federated Graph Condensation with Information Bottleneck Principles AAAI 2025 [PUB]
A High-Efficiency Federated Learning Method Using Complementary Pruning for D2D Communication (Student Abstract) AAAI 2025 [PUB]
Federated Learning with Sample-level Client Drift Mitigation AAAI 2025 [PUB]
Pilot: Building the Federated Multimodal Instruction Tuning Framework AAAI 2025 [PUB]
Flexible Sharpness-Aware Personalized Federated Learning AAAI 2025 [PUB]
MultiSFL: Towards Accurate Split Federated Learning via Multi-Model Aggregation and Knowledge Replay AAAI 2025 [PUB]
PFedCS: A Personalized Federated Learning Method for Enhancing Collaboration among Similar Classifiers AAAI 2025 [PUB]
Federated Graph Anomaly Detection Through Contrastive Learning with Global Negative Pairs AAAI 2025 [PUB]
Fed-DFA: Federated Distillation for Heterogeneous Model Fusion Through the Adversarial Lens AAAI 2025 [PUB]
Federated Recommendation with Explicitly Encoding Item Bias AAAI 2025 [PUB]
Defending Against Sophisticated Poisoning Attacks with RL-based Aggregation in Federated Learning AAAI 2025 [PUB]
Decentralized Federated Learning with Model Caching on Mobile Agents AAAI 2025 [PUB]
Cluster Based Heterogeneous Federated Foundation Model Adaptation and Fine-Tuning AAAI 2025 [PUB]
FedFSL-CFRD: Personalized Federated Few-Shot Learning with Collaborative Feature Representation Disentanglement AAAI 2025 [PUB]
Reinforcement Active Client Selection for Federated Heterogeneous Graph Learning AAAI 2025 [PUB]
Tackling Intertwined Data and Device Heterogeneities in Federated Learning with Unlimited Staleness AAAI 2025 [PUB]
Federated Weakly Supervised Video Anomaly Detection with Multimodal Prompt AAAI 2025 [PUB]
Overcoming Heterogeneous Data in Federated Medical Vision-Language Pre-training: A Triple-Embedding Model Selector Approach AAAI 2025 [PUB]
Reputation-aware Revenue Allocation for Auction-based Federated Learning AAAI 2025 [PUB]
Learn How to Query from Unlabeled Data Streams in Federated Learning AAAI 2025 [PUB]
Efficient Federated Learning via Clients-to-Server Knowledge Distillation (Student Abstract) AAAI 2025 [PUB]
Graph Consistency and Diversity Measurement for Federated Multi-View Clustering AAAI 2025 [PUB]
WHALE-FL: Wireless and Heterogeneity Aware Latency Efficient Federated Learning over Mobile Devices via Adaptive Subnetwork Scheduling AAAI 2025 [PUB]
Label-Free Backdoor Attacks in Vertical Federated Learning AAAI 2025 [PUB]
Incongruent Multimodal Federated Learning for Medical Vision and Language-based Multi-label Disease Detection AAAI 2025 [PUB]
FedPIA – Permuting and Integrating Adapters Leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning AAAI 2025 [PUB]
Fair Federated Survival Analysis AAAI 2025 [PUB]
Federated t-SNE and UMAP for Distributed Data Visualization AAAI 2025 [PUB]
Cross-Silo Feature Space Alignment for Federated Learning on Clients with Imbalanced Data AAAI 2025 [PUB]
Federated Unsupervised Domain Generalization Using Global and Local Alignment of Gradients AAAI 2025 [PUB]
In-depth Analysis of Low-rank Matrix Factorisation in a Federated Setting AAAI 2025 [PUB]
Look Back for More: Harnessing Historical Sequential Updates for Personalized Federated Adapter Tuning AAAI 2025 [PUB]
Breaking Data Silos in Parkinson’s Disease Diagnosis: An Adaptive Federated Learning Approach for Privacy-Preserving Facial Expression Analysis AAAI 2025 [PUB]
Federated Unlearning with Gradient Descent and Conflict Mitigation AAAI 2025 [PUB]
Dual-calibrated Co-training Framework for Personalized Federated Semi-Supervised Medical Image Segmentation AAAI 2025 [PUB]
FedSPU: Personalized Federated Learning for Resource-Constrained Devices with Stochastic Parameter Update AAAI 2025 [PUB]
FedSum: Data-Efficient Federated Learning Under Data Scarcity Scenario for Text Summarization AAAI 2025 [PUB]
Data-Free Black-Box Federated Learning via Zeroth-Order Gradient Estimation AAAI 2025 [PUB]
FedCross: Intertemporal Federated Learning Under Evolutionary Games AAAI 2025 [PUB]
Exploit Gradient Skewness to Circumvent Byzantine Defenses for Federated Learning AAAI 2025 [PUB]
SemiDFL: A Semi-Supervised Paradigm for Decentralized Federated Learning AAAI 2025 [PUB]
Personalized Federated Learning for Spatio-Temporal Forecasting: A Dual Semantic Alignment-Based Contrastive Approach AAAI 2025 [PUB]
Federated Graph-Level Clustering Network AAAI 2025 [PUB]
LiD-FL: Towards List-Decodable Federated Learning AAAI 2025 [PUB]
Convergence Analysis of Federated Learning Methods Using Backward Error Analysis AAAI 2025 [PUB]
Progressive Distribution Matching for Federated Semi-Supervised Learning AAAI 2025 [PUB]
TTA-FedDG: Leveraging Test-Time Adaptation to Address Federated Domain Generalization AAAI 2025 [PUB]
Personalized Federated Collaborative Filtering: A Variational AutoEncoder Approach AAAI 2025 [PUB]
EBS-CFL: Efficient and Byzantine-robust Secure Clustered Federated Learning AAAI 2025 [PUB]
FedMSGL: A Self-Expressive Hypergraph Based Federated Multi-View Learning AAAI 2025 [PUB]
pFedGPA: Diffusion-based Generative Parameter Aggregation for Personalized Federated Learning AAAI 2025 [PUB]
FCOM: A Federated Collaborative Online Monitoring Framework via Representation Learning AAAI 2025 [PUB]
FedCFA: Alleviating Simpson’s Paradox in Model Aggregation with Counterfactual Federated Learning AAAI 2025 [PUB]
Federated Learning with Heterogeneous LLMs: Integrating Small Student Client Models with a Large Hungry Model AAAI 2025 [PUB]
PA3Fed: Period-Aware Adaptive Aggregation for Improved Federated Learning AAAI 2025 [PUB]
TRAIL: Trust-Aware Client Scheduling for Semi-Decentralized Federated Learning AAAI 2025 [PUB]
FedAA: A Reinforcement Learning Perspective on Adaptive Aggregation for Fair and Robust Federated Learning AAAI 2025 [PUB]
DCHM: Dynamic Collaboration of Heterogeneous Models Through Isomerism Learning in a Blockchain-Powered Federated Learning Framework AAAI 2025 [PUB]
Federated Assemblies AAAI 2025 [PUB]
Federated Causally Invariant Feature Learning AAAI 2025 [PUB]
A New Federated Learning Framework Against Gradient Inversion Attacks AAAI 2025 [PUB]
Exploring Vacant Classes in Label-Skewed Federated Learning AAAI 2025 [PUB]
Capture Global Feature Statistics for One-Shot Federated Learning AAAI 2025 [PUB]
Multimodal Fusion Using Multi-View Domains for Data Heterogeneity in Federated Learning AAAI 2025 [PUB]
MFL-Owner: Ownership Protection for Multi-modal Federated Learning via Orthogonal Transform Watermark AAAI 2025 [PUB]
Virtual Nodes Can Help: Tackling Distribution Shifts in Federated Graph Learning AAAI 2025 [PUB]
Beyond Federated Prototype Learning: Learnable Semantic Anchors with Hyperspherical Contrast for Domain-Skewed Data AAAI 2025 [PUB]
Scalable Federated One-Step Multi-View Clustering with Tensorized Regularization AAAI 2025 [PUB]
SADBA: Self-Adaptive Distributed Backdoor Attack Against Federated Learning AAAI 2025 [PUB]
Large Language Models Enhanced Personalized Graph Neural Architecture Search in Federated Learning AAAI 2025 [PUB]
How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? AAAI 2025 [PUB]
Attribute Inference Attacks for Federated Regression Tasks AAAI 2025 [PUB]
Federated Binary Matrix Factorization Using Proximal Optimization AAAI 2025 [PUB]
Creating Coherence in Federated Non-Negative Matrix Factorization AAAI 2025 [PUB]
Rethinking the Starting Point: Collaborative Pre-Training for Federated Downstream Tasks AAAI 2025 [PUB]
DualGFL: Federated Learning with a Dual-Level Coalition-Auction Game AAAI 2025 [PUB]
Federated Foundation Models on Heterogeneous Time Series AAAI 2025 [PUB]
FedPop: Federated Population-based Hyperparameter Tuning AAAI 2025 [PUB]
Enhancing Privacy in the Early Detection of Sexual Predators Through Federated Learning and Differential Privacy AAAI 2025 [PUB]
EFSkip: A New Error Feedback with Linear Speedup for Compressed Federated Learning with Arbitrary Data Heterogeneity AAAI 2025 [PUB]
Little Is Enough: Boosting Privacy by Sharing Only Hard Labels in Federated Semi-Supervised Learning AAAI 2025 [PUB]
Federated Multi-View Clustering via Tensor Factorization IJCAI 2024 [PUB]
Efficient Federated Multi-View Clustering with Integrated Matrix Factorization and K-Means IJCAI 2024 [PUB]
LG-FGAD: An Effective Federated Graph Anomaly Detection Framework IJCAI 2024 [PUB]
Federated Prompt Learning for Weather Foundation Models on Devices IJCAI 2024 [PUB]
Breaking Barriers of System Heterogeneity: Straggler-Tolerant Multimodal Federated Learning via Knowledge Distillation IJCAI 2024 [PUB]
Unlearning during Learning: An Efficient Federated Machine Unlearning Method IJCAI 2024 [PUB]
Practical Hybrid Gradient Compression for Federated Learning Systems IJCAI 2024 [PUB]
Sample Quality Heterogeneity-aware Federated Causal Discovery through Adaptive Variable Space Selection IJCAI 2024 [PUB] [CODE]
Feature Norm Regularized Federated Learning: Utilizing Data Disparities for Model Performance Gains IJCAI 2024 [PUB] [CODE]
Dirichlet-based Uncertainty Quantification for Personalized Federated Learning with Improved Posterior Networks IJCAI 2024 [PUB]
FedConPE: Efficient Federated Conversational Bandits with Heterogeneous Clients IJCAI 2024 [PUB]
DarkFed: A Data-Free Backdoor Attack in Federated Learning IJCAI 2024 [PUB]
Scalable Federated Unlearning via Isolated and Coded Sharding IJCAI 2024 [PUB]
Enhancing Dual-Target Cross-Domain Recommendation with Federated Privacy-Preserving Learning IJCAI 2024 [PUB]
Label Leakage in Vertical Federated Learning: A Survey IJCAI 2024 [PUB]
The Rise of Federated Intelligence: From Federated Foundation Models Toward Collective Intelligence IJCAI 2024 [PUB]
LEAP: Optimization Hierarchical Federated Learning on Non-IID Data with Coalition Formation Game IJCAI 2024 [PUB]
EAB-FL: Exacerbating Algorithmic Bias through Model Poisoning Attacks in Federated Learning IJCAI 2024 [PUB]
Knowledge Distillation in Federated Learning: A Practical Guide IJCAI 2024 [PUB]
FedGCS: A Generative Framework for Efficient Client Selection in Federated Learning via Gradient-based Optimization IJCAI 2024 [PUB]
FedPFT: Federated Proxy Fine-Tuning of Foundation Models IJCAI 2024 [PUB] [CODE]
A Systematic Survey on Federated Semi-supervised Learning IJCAI 2024 [PUB]
Intelligent Agents for Auction-based Federated Learning: A Survey IJCAI 2024 [PUB]
A Bias-Free Revenue-Maximizing Bidding Strategy for Data Consumers in Auction-based Federated Learning IJCAI 2024 [PUB]
Dual Calibration-based Personalised Federated Learning IJCAI 2024 [PUB]
Stakeholder-oriented Decision Support for Auction-based Federated Learning IJCAI 2024 [PUB]
Redefining Contributions: Shapley-Driven Federated Learning IJCAI 2024 [PUB] [CODE]
A Survey on Efficient Federated Learning Methods for Foundation Model Training IJCAI 2024 [PUB]
From Optimization to Generalization: Fair Federated Learning against Quality Shift via Inter-Client Sharpness Matching IJCAI 2024 [PUB] [CODE]
FBLG: A Local Graph Based Approach for Handling Dual Skewed Non-IID Data in Federated Learning IJCAI 2024 [PUB]
FedFa: A Fully Asynchronous Training Paradigm for Federated Learning IJCAI 2024 [PUB]
FedSSA: Semantic Similarity-based Aggregation for Efficient Model-Heterogeneous Personalized Federated Learning IJCAI 2024 [PUB]
FedES: Federated Early-Stopping for Hindering Memorizing Heterogeneous Label Noise IJCAI 2024 [PUB]
Personalized Federated Learning for Cross-City Traffic Prediction IJCAI 2024 [PUB]
Federated Adaptation for Foundation Model-based Recommendations IJCAI 2024 [PUB]
BADFSS: Backdoor Attacks on Federated Self-Supervised Learning IJCAI 2024 [PUB]
Estimating before Debiasing: A Bayesian Approach to Detaching Prior Bias in Federated Semi-Supervised Learning IJCAI 2024 [PUB] [CODE]
FedTAD: Topology-aware Data-free Knowledge Distillation for Subgraph Federated Learning IJCAI 2024 [PUB]
BOBA: Byzantine-Robust Federated Learning with Label Skewness UIUC AISTATS 2024 [PUB] [PDF] [CODE]
Federated Linear Contextual Bandits with Heterogeneous Clients University of Virginia AISTATS 2024 [PUB] [PDF] [CODE]
Federated Experiment Design under Distributed Differential Privacy Stanford University; Meta AISTATS 2024 [PUB] [PDF] [CODE]
Escaping Saddle Points in Heterogeneous Federated Learning via Distributed SGD with Communication Compression Princeton University AISTATS 2024 [PUB] [PDF]
Asynchronous SGD on Graphs: a Unified Framework for Asynchronous Decentralized and Federated Optimization INRIA AISTATS 2024 [PUB] [PDF]
SIFU: Sequential Informed Federated Unlearning for Efficient and Provable Client Unlearning in Federated Optimization INRIA AISTATS 2024 [PUB] [PDF] [CODE]
Compression with Exact Error Distribution for Federated Learning École Polytechnique AISTATS 2024 [PUB] [PDF] [CODE]
Adaptive Federated Minimax Optimization with Lower Complexities NJU; MIIT Key Laboratory of Pattern Analysis and Machine Intelligence AISTATS 2024 [PUB] [PDF]
Adaptive Compression in Federated Learning via Side Information Stanford University; University of Padova AISTATS 2024 [PUB] [PDF] [CODE]
On-Demand Federated Learning for Arbitrary Target Class Distributions UNIST AISTATS 2024 [PUB] [CODE]
FedFisher: Leveraging Fisher Information for One-Shot Federated Learning CMU AISTATS 2024 [PUB] [PDF] [CODE]
Queuing dynamics of asynchronous Federated Learning Huawei AISTATS 2024 [PUB] [PDF]
Personalized Federated X-armed Bandit Purdue University AISTATS 2024 [PUB] [PDF] [CODE]
Federated Learning For Heterogeneous Electronic Health Records Utilising Augmented Temporal Graph Attention Networks University of Oxford AISTATS 2024 [PUB] [CODE]
Stochastic Smoothed Gradient Descent Ascent for Federated Minimax Optimization University of Virginia AISTATS 2024 [PUB] [PDF]
Understanding Generalization of Federated Learning via Stability: Heterogeneity Matters Northwestern University AISTATS 2024 [PUB] [PDF] [CODE]
Provable Mutual Benefits from Federated Learning in Privacy-Sensitive Domains Sofia University AISTATS 2024 [PUB] [PDF] [CODE]
Analysis of Privacy Leakage in Federated Large Language Models University of Florida AISTATS 2024 [PUB] [PDF] [CODE]
Invariant Aggregator for Defending against Federated Backdoor Attacks UIUC AISTATS 2024 [PUB] [PDF] [CODE]
Communication-Efficient Federated Learning With Data and Client Heterogeneity ISTA AISTATS 2024 [PUB] [PDF] [CODE]
FedMut: Generalized Federated Learning via Stochastic Mutation NTU AAAI 2024 [PUB]
Federated Partial Label Learning with Local-Adaptive Augmentation and Regularization Carleton University AAAI 2024 [PUB] [PAGE]
No Prejudice! Fair Federated Graph Neural Networks for Personalized Recommendation IIT AAAI 2024 [PUB] [PAGE] [PDF] [CODE]
Formal Logic Enabled Personalized Federated Learning through Property Inference Vanderbilt University AAAI 2024 [PUB] [PDF]
Task-Agnostic Privacy-Preserving Representation Learning for Federated Learning against Attribute Inference Attacks Illinois Tech AAAI 2024 [PUB] [PAGE] [PDF] [CODE]
FairTrade: Achieving Pareto-Optimal Trade-Offs between Balanced Accuracy and Fairness in Federated Learning Leibniz University AAAI 2024 [PUB] [PAGE]
Combating Data Imbalances in Federated Semi-supervised Learning with Dual Regulators HKUST AAAI 2024 [PUB] [PAGE] [PDF]
Fed-QSSL: A Framework for Personalized Federated Learning under Bitwidth and Data Heterogeneity UT AAAI 2024 [PUB] [PAGE] [PDF]
On Disentanglement of Asymmetrical Knowledge Transfer for Modality-Task Agnostic Federated Learning University of Virginia AAAI 2024 [PUB]
FedDAT: An Approach for Foundation Model Finetuning in Multi-Modal Heterogeneous Federated Learning LMU Munich Siemens AG AAAI 2024 [PUB] [PAGE] [PDF] [CODE]
Watch Your Head: Assembling Projection Heads to Save the Reliability of Federated Models Xi'an Jiaotong University Shaanxi Joint Key Laboratory for Artificial Intelligence AAAI 2024 [PUB] [PAGE] [PDF]
FedGCR: Achieving Performance and Fairness for Federated Learning with Distinct Client Types via Group Customization and Reweighting NTU AAAI 2024 [PUB] [PAGE] [CODE]
Federated Modality-Specific Encoders and Multimodal Anchors for Personalized Brain Tumor Segmentation Xiamen University AAAI 2024 [PUB] [PAGE] [PDF] [CODE]
Exploiting Label Skews in Federated Learning with Model Concatenation NUS AAAI 2024 [PUB] [PAGE] [PDF] [CODE]
Complementary Knowledge Distillation for Robust and Privacy-Preserving Model Serving in Vertical Federated Learning SUST; HKUST AAAI 2024 [PUB] [PAGE]
Federated Learning via Input-Output Collaborative Distillation University at Buffalo; USA Harvard Medical School AAAI 2024 [PUB] [PAGE] [PDF] [CODE]
Calibrated One Round Federated Learning with Bayesian Inference in the Predictive Space University of Waterloo Vector Institute AAAI 2024 [PUB] [PAGE] [PDF] [CODE]
FedCSL: A Scalable and Accurate Approach to Federated Causal Structure Learning HFUT AAAI 2024 [PUB] [PDF]
FedFixer: Mitigating Heterogeneous Label Noise in Federated Learning Xi'an Jiaotong University; Leiden University AAAI 2024 [PUB] [PAGE] [PDF]
FedLPS: Heterogeneous Federated Learning for Multiple Tasks with Local Parameter Sharing NJU AAAI 2024 [PUB] [PAGE] [PDF] [CODE]
Provably Convergent Federated Trilevel Learning TJU AAAI 2024 [PUB] [PDF]
Performative Federated Learning: A Solution to Model-Dependent and Heterogeneous Distribution Shifts U-M AAAI 2024 [PUB] [PAGE]
General Commerce Intelligence: Glocally Federated NLP-Based Engine for Privacy-Preserving and Sustainable Personalized Services of Multi-Merchants Kyung Hee University; Harex InfoTech AAAI 2024 [PUB] [PAGE]
EMGAN: Early-Mix-GAN on Extracting Server-Side Model in Split Federated Learning Sony AI AAAI 2024 [PUB] [PAGE] [CODE]
FedDiv: Collaborative Noise Filtering for Federated Learning with Noisy Labels SYSU; HKU AAAI 2024 [PUB] [PAGE] [PDF] [CODE]
Point Transformer with Federated Learning for Predicting Breast Cancer HER2 Status from Hematoxylin and Eosin-Stained Whole Slide Images USTC; CAS AAAI 2024 [PUB] [PAGE] [PDF] [CODE]
FedNS: A Fast Sketching Newton-Type Algorithm for Federated Learning CAS AAAI 2024 [PUB] [PDF] [CODE]
Federated X-armed Bandit Purdue University AAAI 2024 [PUB] [PAGE] [PDF] [CODE]
Algorithmic Foundation of Federated Learning with Sequential Data GMU AAAI 2024 [PUB]
UFDA: Universal Federated Domain Adaptation with Practical Assumptions XJTU; University of Sydney AAAI 2024 [PUB] [PAGE] [PDF] [CODE]
FedASMU: Efficient Asynchronous Federated Learning with Dynamic Staleness-Aware Model Update Hithink RoyalFlush Information Network Co AAAI 2024 [PUB] [PAGE] [PDF]
Language-Guided Transformer for Federated Multi-Label Classification NTU AAAI 2024 [PUB] [PAGE] [PDF] [CODE]
FedCD: Federated Semi-Supervised Learning with Class Awareness Balance via Dual Teachers SZU AAAI 2024 [PUB] [PAGE] [CODE]
Beyond Traditional Threats: A Persistent Backdoor Attack on Federated Learning HEU AAAI 2024 [PUB] [PAGE] [CODE]
Federated Learning with Extremely Noisy Clients via Negative Distillation XMU AAAI 2024 [PUB] [PAGE] [PDF] [CODE]
FedST: Federated Style Transfer Learning for Non-IID Image Segmentation USTB AAAI 2024 [PUB] [PAGE] [学报] [CODE]
PPIDSG: A Privacy-Preserving Image Distribution Sharing Scheme with GAN in Federated Learning USTC AAAI 2024 [PUB] [PAGE] [PDF] [CODE]
A Privacy Preserving Federated Learning (PPFL) Based Cognitive Digital Twin (CDT) Framework for Smart Cities DCU AAAI 2024 [PUB]
A Primal-Dual Algorithm for Hybrid Federated Learning Northwestern University AAAI 2024 [PUB] [PAGE] [PDF]
FedLF: Layer-Wise Fair Federated Learning CUHK; Shenzhen Institute of Artificial Intelligence and Robotics for Society AAAI 2024 [PUB] [PAGE]
Towards Fair Graph Federated Learning via Incentive Mechanisms ZJU; FDU AAAI 2024 [PUB] [PAGE] [PDF] [CODE]
Towards the Robustness of Differentially Private Federated Learning THU AAAI 2024 [PUB] [PAGE]
Resisting Backdoor Attacks in Federated Learning via Bidirectional Elections and Individual Perspective ZJU; HUAWEI AAAI 2024 [PUB] [PAGE] [PDF] [CODE]
Integer Is Enough: When Vertical Federated Learning Meets Rounding ZJU; Ant Group AAAI 2024 [PUB] [PAGE]
CLIP-Guided Federated Learning on Heterogeneity and Long-Tailed Data XMU AAAI 2024 [PUB] [PAGE] [PDF] [CODE]
Federated Adaptive Prompt Tuning for Multi-Domain Collaborative Learning FDU AAAI 2024 [PUB] [PAGE] [PDF] [CODE]
Multi-Dimensional Fair Federated Learning SDU AAAI 2024 [PUB] [PAGE] [PDF]
HiFi-Gas: Hierarchical Federated Learning Incentive Mechanism Enhanced Gas Usage Estimation ENN Group AAAI 2024 [PUB]
On the Role of Server Momentum in Federated Learning University of Virginia AAAI 2024 [PUB] [PDF]
FedCompetitors: Harmonious Collaboration in Federated Learning with Competing Participants BUPT AAAI 2024 [PUB] [PAGE] [PDF]
z-SignFedAvg: A Unified Stochastic Sign-Based Compression for Federated Learning CUHK; China Shenzhen Research Institute of Big Data AAAI 2024 [PUB] [PAGE] [PDF]
Data Disparity and Temporal Unavailability Aware Asynchronous Federated Learning for Predictive Maintenance on Transportation Fleets Volkswagen Group AAAI 2024 [PUB] [PAGE]
Federated Graph Learning under Domain Shift with Generalizable Prototypes WHU AAAI 2024 [PUB] [PAGE]
TurboSVM-FL: Boosting Federated Learning through SVM Aggregation for Lazy Clients Technical University of Munich AAAI 2024 [PUB] [PAGE] [PDF] [CODE]
Multi-Source Collaborative Gradient Discrepancy Minimization for Federated Domain Generalization TJU AAAI 2024 [PUB] [PDF] [CODE]
Concealing Sensitive Samples against Gradient Leakage in Federated Learning Monash University AAAI 2024 [PUB] [PAGE] [PDF] [CODE]
FedA3I: Annotation Quality-Aware Aggregation for Federated Medical Image Segmentation against Heterogeneous Annotation Noise HUST AAAI 2024 [PUB] [PAGE] [PDF] [CODE]
Federated Causality Learning with Explainable Adaptive Optimization SDU AAAI 2024 [PUB] [PAGE] [PDF]
Federated Contextual Cascading Bandits with Asynchronous Communication and Heterogeneous Users USTC AAAI 2024 [PUB] [PAGE] [PDF]
Exploring One-Shot Semi-supervised Federated Learning with Pre-trained Diffusion Models FDU AAAI 2024 [PUB] [PDF]
Diversity-Authenticity Co-constrained Stylization for Federated Domain Generalization in Person Re-identification XMU; University of Trento AAAI 2024 [PUB] [PAGE]
PerFedRLNAS: One-for-All Personalized Federated Neural Architecture Search U of T AAAI 2024 [PUB] [PAGE]
Efficient Asynchronous Federated Learning with Prospective Momentum Aggregation and Fine-Grained Correction BUPT AAAI 2024 [PUB] [PAGE]
Adversarial Attacks on Federated-Learned Adaptive Bitrate Algorithms HKU AAAI 2024 [PUB]
FedTGP: Trainable Global Prototypes with Adaptive-Margin-Enhanced Contrastive Learning for Data and Model Heterogeneity in Federated Learning SJTU AAAI 2024 [PUB] [PAGE] [PDF] [CODE]
LR-XFL: Logical Reasoning-Based Explainable Federated Learning NTU AAAI 2024 [PUB] [PDF] [CODE]
A Huber Loss Minimization Approach to Byzantine Robust Federated Learning Zhejiang Lab AAAI 2024 [PUB] [PAGE] [PDF]
Knowledge-Aware Parameter Coaching for Personalized Federated Learning Northeastern University AAAI 2024 [PUB] [PAGE]
Federated Label-Noise Learning with Local Diversity Product Regularization SJTU AAAI 2024 [PUB] [PAGE] [SUPP]
Adapted Weighted Aggregation in Federated Learning (Student Abstract) UBC AAAI 2024 [PUB]
Knowledge Transfer via Compact Model in Federated Learning (Student Abstract) University of Sydney AAAI 2024 [PUB] [PAGE]
PICSR: Prototype-Informed Cross-Silo Router for Federated Learning (Student Abstract) The Ohio State University Auton Lab, CMU AAAI 2024 [PUB] [PAGE]
Privacy-preserving graph convolution network for federated item recommendation SZU AI 2023 [PUB]
Win-Win: A Privacy-Preserving Federated Framework for Dual-Target Cross-Domain Recommendation CAS; UCAS; JD Technology; JD Intelligent Cities Research AAAI 2023 [PUB]
Untargeted Attack against Federated Recommendation Systems via Poisonous Item Embeddings and the Defense USTC; State Key Laboratory of Cognitive Intelligence AAAI 2023 [PUB] [PDF] [CODE]
Incentive-Boosted Federated Crowdsourcing SDU AAAI 2023 [PUB] [PDF]
Tackling Data Heterogeneity in Federated Learning with Class Prototypes Lehigh University AAAI 2023 [PUB] [PDF] [CODE]
FairFed: Enabling Group Fairness in Federated Learning USC AAAI 2023 [PUB] [PDF] [解读]
Federated Robustness Propagation: Sharing Adversarial Robustness in Heterogeneous Federated Learning MSU AAAI 2023 [PUB]
Complement Sparsification: Low-Overhead Model Pruning for Federated Learning NJIT AAAI 2023 [PUB]
Almost Cost-Free Communication in Federated Best Arm Identification NUS AAAI 2023 [PUB] [PDF]
Layer-Wise Adaptive Model Aggregation for Scalable Federated Learning University of Southern California Inha University AAAI 2023 [PUB] [PDF]
Poisoning with Cerberus: Stealthy and Colluded Backdoor Attack against Federated Learning BJTU AAAI 2023 [PUB]
FedMDFG: Federated Learning with Multi-Gradient Descent and Fair Guidance CUHK; The Shenzhen Institute of Artificial Intelligence and Robotics for Society AAAI 2023 [PUB]
Securing Secure Aggregation: Mitigating Multi-Round Privacy Leakage in Federated Learning USC AAAI 2023 [PUB] [PDF] [VIDEO] [CODE]
Federated Learning on Non-IID Graphs via Structural Knowledge Sharing UTS AAAI 2023 [PUB] [PDF] [CODE]
Efficient Distribution Similarity Identification in Clustered Federated Learning via Principal Angles between Client Data Subspaces UCSD AAAI 2023 [PUB] [PDF] [CODE]
FedABC: Targeting Fair Competition in Personalized Federated Learning WHU; Hubei Luojia Laboratory; JD Explore Academy AAAI 2023 [PUB] [PDF]
Beyond ADMM: A Unified Client-Variance-Reduced Adaptive Federated Learning Framework SUTD AAAI 2023 [PUB] [PDF]
FedGS: Federated Graph-Based Sampling with Arbitrary Client Availability XMU AAAI 2023 [PUB] [PDF] [CODE]
Faster Adaptive Federated Learning University of Pittsburgh AAAI 2023 [PUB] [PDF]
FedNP: Towards Non-IID Federated Learning via Federated Neural Propagation HKUST AAAI 2023 [PUB] [CODE] [VIDEO] [SUPP]
Bayesian Federated Neural Matching That Completes Full Information TJU AAAI 2023 [PUB] [PDF]
CDMA: A Practical Cross-Device Federated Learning Algorithm for General Minimax Problems ZJU AAAI 2023 [PUB] [PDF] [CODE]
Federated Generative Model on Multi-Source Heterogeneous Data in IoT GSU AAAI 2023 [PUB]
DeFL: Defending against Model Poisoning Attacks in Federated Learning via Critical Learning Periods Awareness SUNY-Binghamton University AAAI 2023 [PUB]
FedALA: Adaptive Local Aggregation for Personalized Federated Learning SJTU AAAI 2023 [PUB] [PDF] [CODE]
Delving into the Adversarial Robustness of Federated Learning ZJU AAAI 2023 [PUB] [PDF]
On the Vulnerability of Backdoor Defenses for Federated Learning TJU AAAI 2023 [PUB] [PDF] [CODE]
Echo of Neighbors: Privacy Amplification for Personalized Private Federated Learning with Shuffle Model RUC; Engineering Research Center of Ministry of Education on Database and BI AAAI 2023 [PUB] [PDF]
DPAUC: Differentially Private AUC Computation in Federated Learning ByteDance Inc. AAAI Special Tracks 2023 [PUB] [PDF] [CODE]
Efficient Training of Large-Scale Industrial Fault Diagnostic Models through Federated Opportunistic Block Dropout NTU AAAI Special Programs 2023 [PUB] [PDF]
Industry-Scale Orchestrated Federated Learning for Drug Discovery KU Leuven AAAI Special Programs 2023 [PUB] [PDF] [VIDEO]
A Federated Learning Monitoring Tool for Self-Driving Car Simulation (Student Abstract) CNU AAAI Special Programs 2023 [PUB]
MGIA: Mutual Gradient Inversion Attack in Multi-Modal Federated Learning (Student Abstract) PolyU AAAI Special Programs 2023 [PUB]
Clustered Federated Learning for Heterogeneous Data (Student Abstract) RUC AAAI Special Programs 2023 [PUB]
FedSampling: A Better Sampling Strategy for Federated Learning THU IJCAI 2023 [PUB] [PDF] [CODE]
HyperFed: Hyperbolic Prototypes Exploration with Consistent Aggregation for Non-IID Data in Federated Learning ZJU IJCAI 2023 [PUB] [PDF]
FedOBD: Opportunistic Block Dropout for Efficiently Training Large-scale Neural Networks through Federated Learning NTU IJCAI 2023 [PUB] [PDF] [CODE]
Federated Probabilistic Preference Distribution Modelling with Compactness Co-Clustering for Privacy-Preserving Multi-Domain Recommendation ZJU IJCAI 2023 [PUB]
Federated Graph Semantic and Structural Learning WHU IJCAI 2023 [PUB]
BARA: Efficient Incentive Mechanism with Online Reward Budget Allocation in Cross-Silo Federated Learning SYSU IJCAI 2023 [PUB] [PDF]
FedDWA: Personalized Federated Learning with Dynamic Weight Adjustment SYSU IJCAI 2023 [PUB] [PDF]
FedPass: Privacy-Preserving Vertical Federated Deep Learning with Adaptive Obfuscation Webank IJCAI 2023 [PUB] [PDF]
Globally Consistent Federated Graph Autoencoder for Non-IID Graphs FZU IJCAI 2023 [PUB] [CODE]
Competitive-Cooperative Multi-Agent Reinforcement Learning for Auction-based Federated Learning NTU IJCAI 2023 [PUB]
Dual Personalization on Federated Recommendation JLU; University of Technology Sydney IJCAI 2023 [PUB] [PDF] [CODE]
FedNoRo: Towards Noise-Robust Federated Learning by Addressing Class Imbalance and Label Noise Heterogeneity HUST IJCAI 2023 [PUB] [PDF] [CODE]
Denial-of-Service or Fine-Grained Control: Towards Flexible Model Poisoning Attacks on Federated Learning Xiangtan University IJCAI 2023 [PUB] [PDF] [CODE]
FedHGN: A Federated Framework for Heterogeneous Graph Neural Networks CUHK IJCAI 2023 [PUB] [PDF] [CODE]
FedET: A Communication-Efficient Federated Class-Incremental Learning Framework Based on Enhanced Transformer Ping An Technology; THU IJCAI 2023 [PUB] [PDF]
Prompt Federated Learning for Weather Forecasting: Toward Foundation Models on Meteorological Data UTS IJCAI 2023 [PUB] [PDF] [CODE]
FedBFPT: An Efficient Federated Learning Framework for Bert Further Pre-training ZJU IJCAI 2023 [PUB] [CODE]
Bayesian Federated Learning: A Survey IJCAI Survey Track 2023 [PDF]
A Survey of Federated Evaluation in Federated Learning Macquarie University IJCAI Survey Track 2023 [PUB] [PDF]
SAMBA: A Generic Framework for Secure Federated Multi-Armed Bandits (Extended Abstract) INSA Centre Val de Loire IJCAI Journal Track 2023 [PUB]
The communication cost of security and privacy in federated frequency estimation Stanford AISTATS 2023 [PUB] [CODE]
Efficient and Light-Weight Federated Learning via Asynchronous Distributed Dropout Rice University AISTATS 2023 [PUB] [CODE]
Federated Learning under Distributed Concept Drift CMU AISTATS 2023 [PUB] [CODE]
Characterizing Internal Evasion Attacks in Federated Learning CMU AISTATS 2023 [PUB] [CODE]
Federated Asymptotics: a model to compare federated learning algorithms Stanford AISTATS 2023 [PUB] [CODE]
Private Non-Convex Federated Learning Without a Trusted Server USC AISTATS 2023 [PUB] [CODE]
Federated Learning for Data Streams Universit ́ e Cˆ ote d’Azur AISTATS 2023 [PUB] [CODE]
Nothing but Regrets — Privacy-Preserving Federated Causal Discovery Helmholtz Centre for Information Security AISTATS 2023 [PUB] [CODE]
Active Membership Inference Attack under Local Differential Privacy in Federated Learning UFL AISTATS 2023 [PUB] [CODE]
Federated Averaging Langevin Dynamics: Toward a unified theory and new algorithms CMAP AISTATS 2023 [PUB]
Byzantine-Robust Federated Learning with Optimal Statistical Rates UC Berkeley AISTATS 2023 [PUB] [CODE]
Federated Learning on Non-IID Graphs via Structural Knowledge Sharing UTS AAAI 2023 [PDF] [CODE]
FedGS: Federated Graph-based Sampling with Arbitrary Client Availability XMU AAAI 2023 [PDF] [CODE]
Incentive-boosted Federated Crowdsourcing SDU AAAI 2023 [PDF]
Towards Understanding Biased Client Selection in Federated Learning. CMU AISTATS 2022 [PUB] [CODE]
FLIX: A Simple and Communication-Efficient Alternative to Local Methods in Federated Learning KAUST AISTATS 2022 [PUB] [PDF] [CODE]
Sharp Bounds for Federated Averaging (Local SGD) and Continuous Perspective. Stanford AISTATS 2022 [PUB] [PDF] [CODE]
Federated Reinforcement Learning with Environment Heterogeneity. PKU AISTATS 2022 [PUB] [PDF] [CODE]
Federated Myopic Community Detection with One-shot Communication Purdue AISTATS 2022 [PUB] [PDF]
Asynchronous Upper Confidence Bound Algorithms for Federated Linear Bandits. University of Virginia AISTATS 2022 [PUB] [PDF] [CODE]
Towards Federated Bayesian Network Structure Learning with Continuous Optimization. CMU AISTATS 2022 [PUB] [PDF] [CODE]
Federated Learning with Buffered Asynchronous Aggregation Meta AI AISTATS 2022 [PUB] [PDF] [VIDEO]
Differentially Private Federated Learning on Heterogeneous Data. Stanford AISTATS 2022 [PUB] [PDF] [CODE]
SparseFed: Mitigating Model Poisoning Attacks in Federated Learning with Sparsification Princeton AISTATS 2022 [PUB] [PDF] [CODE] [VIDEO]
Basis Matters: Better Communication-Efficient Second Order Methods for Federated Learning KAUST AISTATS 2022 [PUB] [PDF]
Federated Functional Gradient Boosting. University of Pennsylvania AISTATS 2022 [PUB] [PDF] [CODE]
QLSD: Quantised Langevin Stochastic Dynamics for Bayesian Federated Learning. Criteo AI Lab AISTATS 2022 [PUB] [PDF] [CODE] [VIDEO]
Meta-Learning Based Knowledge Extrapolation for Knowledge Graphs in the Federated Setting kg. ZJU IJCAI 2022 [PUB] [PDF] [CODE]
Personalized Federated Learning With a Graph UTS IJCAI 2022 [PUB] [PDF] [CODE]
Vertically Federated Graph Neural Network for Privacy-Preserving Node Classification ZJU IJCAI 2022 [PUB] [PDF]
Adapt to Adaptation: Learning Personalization for Cross-Silo Federated Learning IJCAI 2022 [PUB] [PDF] [CODE]
Heterogeneous Ensemble Knowledge Transfer for Training Large Models in Federated Learning IJCAI 2022 [PUB] [PDF]
Private Semi-Supervised Federated Learning. IJCAI 2022 [PUB]
Continual Federated Learning Based on Knowledge Distillation. IJCAI 2022 [PUB]
Federated Learning on Heterogeneous and Long-Tailed Data via Classifier Re-Training with Federated Features IJCAI 2022 [PUB] [PDF] [CODE]
Federated Multi-Task Attention for Cross-Individual Human Activity Recognition IJCAI 2022 [PUB]
Personalized Federated Learning with Contextualized Generalization. IJCAI 2022 [PUB] [PDF]
Shielding Federated Learning: Robust Aggregation with Adaptive Client Selection. IJCAI 2022 [PUB] [PDF]
FedCG: Leverage Conditional GAN for Protecting Privacy and Maintaining Competitive Performance in Federated Learning IJCAI 2022 [PUB] [PDF] [CODE]
FedDUAP: Federated Learning with Dynamic Update and Adaptive Pruning Using Shared Data on the Server. IJCAI 2022 [PUB] [PDF]
Towards Verifiable Federated Learning surv. IJCAI 2022 [PUB] [PDF]
HarmoFL: Harmonizing Local and Global Drifts in Federated Learning on Heterogeneous Medical Images CUHK; BUAA AAAI 2022 [PUB] [PDF] [CODE] [解读]
Federated Learning for Face Recognition with Gradient Correction BUPT AAAI 2022 [PUB] [PDF]
SpreadGNN: Decentralized Multi-Task Federated Learning for Graph Neural Networks on Molecular Data USC AAAI 2022 [PUB] [PDF] [CODE] [解读]
SmartIdx: Reducing Communication Cost in Federated Learning by Exploiting the CNNs Structures HIT; PCL AAAI 2022 [PUB] [CODE]
Bridging between Cognitive Processing Signals and Linguistic Features via a Unified Attentional Network TJU AAAI 2022 [PUB] [PDF]
Seizing Critical Learning Periods in Federated Learning SUNY-Binghamton University AAAI 2022 [PUB] [PDF]
Coordinating Momenta for Cross-silo Federated Learning University of Pittsburgh AAAI 2022 [PUB] [PDF]
FedProto: Federated Prototype Learning over Heterogeneous Devices UTS AAAI 2022 [PUB] [PDF] [CODE]
FedSoft: Soft Clustered Federated Learning with Proximal Local Updating CMU AAAI 2022 [PUB] [PDF] [CODE]
Federated Dynamic Sparse Training: Computing Less, Communicating Less, Yet Learning Better The University of Texas at Austin AAAI 2022 [PUB] [PDF] [CODE]
FedFR: Joint Optimization Federated Framework for Generic and Personalized Face Recognition National Taiwan University AAAI 2022 [PUB] [PDF] [CODE]
SplitFed: When Federated Learning Meets Split Learning CSIRO AAAI 2022 [PUB] [PDF] [CODE]
Efficient Device Scheduling with Multi-Job Federated Learning Soochow University AAAI 2022 [PUB] [PDF]
Implicit Gradient Alignment in Distributed and Federated Learning IIT Kanpur AAAI 2022 [PUB] [PDF]
Federated Nearest Neighbor Classification with a Colony of Fruit-Flies IBM Research AAAI 2022 [PUB] [PDF] [CODE]
Iterated Vector Fields and Conservatism, with Applications to Federated Learning. Google ALT 2022 [PUB] [PDF]
Federated Learning with Sparsification-Amplified Privacy and Adaptive Optimization IJCAI 2021 [PUB] [PDF] [VIDEO]
Behavior Mimics Distribution: Combining Individual and Group Behaviors for Federated Learning IJCAI 2021 [PUB] [PDF]
FedSpeech: Federated Text-to-Speech with Continual Learning IJCAI 2021 [PUB] [PDF]
Practical One-Shot Federated Learning for Cross-Silo Setting IJCAI 2021 [PUB] [PDF] [CODE]
Federated Model Distillation with Noise-Free Differential Privacy IJCAI 2021 [PUB] [PDF] [VIDEO]
LDP-FL: Practical Private Aggregation in Federated Learning with Local Differential Privacy IJCAI 2021 [PUB] [PDF]
Federated Learning with Fair Averaging. :fire: IJCAI 2021 [PUB] [PDF] [CODE]
H-FL: A Hierarchical Communication-Efficient and Privacy-Protected Architecture for Federated Learning. IJCAI 2021 [PUB] [PDF]
Communication-efficient and Scalable Decentralized Federated Edge Learning. IJCAI 2021 [PUB]
Secure Bilevel Asynchronous Vertical Federated Learning with Backward Updating Xidian University; JD Tech AAAI 2021 [PUB] [PDF] [VIDEO]
FedRec++: Lossless Federated Recommendation with Explicit Feedback SZU AAAI 2021 [PUB] [VIDEO]
Federated Multi-Armed Bandits University of Virginia AAAI 2021 [PUB] [PDF] [CODE] [VIDEO]
On the Convergence of Communication-Efficient Local SGD for Federated Learning Temple University; University of Pittsburgh AAAI 2021 [PUB] [VIDEO]
FLAME: Differentially Private Federated Learning in the Shuffle Model Renmin University of China; Kyoto University AAAI 2021 [PUB] [PDF] [VIDEO] [CODE]
Toward Understanding the Influence of Individual Clients in Federated Learning SJTU; The University of Texas at Dallas AAAI 2021 [PUB] [PDF] [VIDEO]
Provably Secure Federated Learning against Malicious Clients Duke University AAAI 2021 [PUB] [PDF] [VIDEO] [SLIDE]
Personalized Cross-Silo Federated Learning on Non-IID Data Simon Fraser University; McMaster University AAAI 2021 [PUB] [PDF] [VIDEO] [UC.]
Model-Sharing Games: Analyzing Federated Learning under Voluntary Participation Cornell University AAAI 2021 [PUB] [PDF] [CODE] [VIDEO]
Curse or Redemption? How Data Heterogeneity Affects the Robustness of Federated Learning University of Nevada; IBM Research AAAI 2021 [PUB] [PDF] [VIDEO]
Game of Gradients: Mitigating Irrelevant Clients in Federated Learning IIT Bombay; IBM Research AAAI 2021 [PUB] [PDF] [CODE] [VIDEO] [SUPP]
Federated Block Coordinate Descent Scheme for Learning Global and Personalized Models CUHK; Arizona State University AAAI 2021 [PUB] [PDF] [VIDEO] [CODE]
Addressing Class Imbalance in Federated Learning Northwestern University AAAI 2021 [PUB] [PDF] [VIDEO] [CODE] [解读]
Defending against Backdoors in Federated Learning with Robust Learning Rate The University of Texas at Dallas AAAI 2021 [PUB] [PDF] [VIDEO] [CODE]
Free-rider Attacks on Model Aggregation in Federated Learning Accenture Labs AISTATS 2021 [PUB] [PDF] [CODE] [VIDEO] [SUPP]
Federated f-differential privacy University of Pennsylvania AISTATS 2021 [PUB] [CODE] [VIDEO] [SUPP]
Federated learning with compression: Unified analysis and sharp guarantees :fire: The Pennsylvania State University; The University of Texas at Austin AISTATS 2021 [PUB] [PDF] [CODE] [VIDEO] [SUPP]
Shuffled Model of Differential Privacy in Federated Learning UCLA; Google AISTATS 2021 [PUB] [VIDEO] [SUPP]
Convergence and Accuracy Trade-Offs in Federated Learning and Meta-Learning Google AISTATS 2021 [PUB] [PDF] [VIDEO] [SUPP]
Federated Multi-armed Bandits with Personalization University of Virginia; The Pennsylvania State University AISTATS 2021 [PUB] [PDF] [CODE] [VIDEO] [SUPP]
Towards Flexible Device Participation in Federated Learning CMU; SYSU AISTATS 2021 [PUB] [PDF] [VIDEO] [SUPP]
Federated Meta-Learning for Fraudulent Credit Card Detection IJCAI 2020 [PUB] [VIDEO]
A Multi-player Game for Studying Federated Learning Incentive Schemes IJCAI 2020 [PUB] [CODE] [解读]
Practical Federated Gradient Boosting Decision Trees NUS; UWA AAAI 2020 [PUB] [PDF] [CODE]
Federated Learning for Vision-and-Language Grounding Problems PKU; Tencent AAAI 2020 [PUB]
Federated Latent Dirichlet Allocation: A Local Differential Privacy Based Framework BUAA AAAI 2020 [PUB]
Federated Patient Hashing Cornell University AAAI 2020 [PUB]
Robust Federated Learning via Collaborative Machine Teaching Symantec Research Labs; KAUST AAAI 2020 [PUB] [PDF]
FedVision: An Online Visual Object Detection Platform Powered by Federated Learning WeBank AAAI 2020 [PUB] [PDF] [CODE]
FedPAQ: A Communication-Efficient Federated Learning Method with Periodic Averaging and Quantization UC Santa Barbara; UT Austin AISTATS 2020 [PUB] [PDF] [VIDEO] [SUPP]
How To Backdoor Federated Learning :fire: Cornell Tech AISTATS 2020 [PUB] [PDF] [VIDEO] [CODE] [SUPP]
Federated Heavy Hitters Discovery with Differential Privacy RPI; Google AISTATS 2020 [PUB] [PDF] [VIDEO] [SUPP]
Multi-Agent Visualization for Explaining Federated Learning WeBank IJCAI 2019 [PUB] [VIDEO]

fl 在顶级机器学习会议和期刊中

联邦学习相关论文被顶级机器学习（ML）会议和期刊接收，包括 NeurIPS（神经信息处理系统年度会议）、ICML（国际机器学习大会）、ICLR（国际表征学习大会）、COLT（计算学习理论年度会议）、UAI（人工智能不确定性会议）、Machine Learning、JMLR（机器学习研究期刊）、TPAMI（IEEE模式分析与机器智能汇刊）。

fl 在顶级机器学习会议和期刊中
Title Affiliation Venue Year Materials
Near-Optimal Regret Bounds for Federated Multi-armed Bandits with Fully Distributed Communication UAI 2025 [PUB]
FALCON: Adaptive Cross-Domain APT Attack Investigation with Federated Causal Learning UAI 2025 [PUB]
FeDCM: Federated Learning of Deep Causal Generative Models UAI 2025 [PUB]
Federated Rényi Fair Inference in Federated Heterogeneous System UAI 2025 [PUB]
FedSPD: A Soft-clustering Approach for Personalized Decentralized Federated Learning UAI 2025 [PUB]
ELF: Federated Langevin Algorithms with Primal, Dual and Bidirectional Compression UAI 2025 [PUB]
FDR-SVM: A Federated Distributionally Robust Support Vector Machine via a Mixture of Wasserstein Balls Ambiguity Set UAI 2025 [PUB]
Cutting Through Privacy: A Hyperplane-Based Data Reconstruction Attack in Federated Learning UAI 2025 [PUB]
Conformal Prediction for Federated Graph Neural Networks with Missing Neighbor Information UAI 2025 [PUB]
Clients Collaborate: Flexible Differentially Private Federated Learning with Guaranteed Improvement of Utility-Privacy Trade-off SYSU ICML 2025 [PUB] [CODE]
Less is More: Federated Graph Learning with Alleviating Topology Heterogeneity from A Causal Perspective ICML 2025 [PUB]
SecEmb: Sparsity-Aware Secure Federated Learning of On-Device Recommender System with Large Embedding ICML 2025 [PUB] [CODE]
Causality Inspired Federated Learning for OOD Generalization ICML 2025 [PUB]
Improving Generalization in Federated Learning with Highly Heterogeneous Data via Momentum-Based Stochastic Controlled Weight Averaging ICML 2025 [PUB] [CODE]
One-Shot Heterogeneous Federated Learning with Local Model-Guided Diffusion Models ICML 2025 [PUB] [CODE]
FOCoOp: Enhancing Out-of-Distribution Robustness in Federated Prompt Learning for Vision-Language Models ICML 2025 [PUB]
An Effective and Secure Federated Multi-View Clustering Method with Information-Theoretic Perspective ICML 2025 [PUB] [CODE]
Gap-Dependent Bounds for Federated $Q$-Learning ICML 2025 [PUB]
FedBEns: One-Shot Federated Learning based on Bayesian Ensemble ICML 2025 [PUB] [CODE]
NTK-DFL: Enhancing Decentralized Federated Learning in Heterogeneous Settings via Neural Tangent Kernel ICML 2025 [PUB] [CODE]
Federated Learning for Feature Generalization with Convex Constraints ICML 2025 [PUB] [CODE]
Uncertainty-Based Extensible Codebook for Discrete Federated Learning in Heterogeneous Data Silos ICML 2025 [PUB] [CODE]
Towards Trustworthy Federated Learning with Untrusted Participants ICML 2025 [PUB]
Multi-Session Budget Optimization for Forward Auction-based Federated Learning ICML 2025 [PUB]
Federated Disentangled Tuning with Textual Prior Decoupling and Visual Dynamic Adaptation ICML 2025 [PUB] [CODE]
LBI-FL: Low-Bit Integerized Federated Learning with Temporally Dynamic Bit-Width Allocation ICML 2025 [PUB]
Momentum-Driven Adaptivity: Towards Tuning-Free Asynchronous Federated Learning ICML 2025 [PUB]
Differentially Private Federated $k$-Means Clustering with Server-Side Data ICML 2025 [PUB] [CODE]
CAN: Leveraging Clients As Navigators for Generative Replay in Federated Continual Learning ICML 2025 [PUB]
Understanding the Statistical Accuracy-Communication Trade-off in Personalized Federated Learning with Minimax Guarantees ICML 2025 [PUB] [CODE]
$S^2$FGL: Spatial Spectral Federated Graph Learning ICML 2025 [PUB] [CODE]
FSL-SAGE: Accelerating Federated Split Learning via Smashed Activation Gradient Estimation ICML 2025 [PUB] [CODE]
Interaction-Aware Gaussian Weighting for Clustered Federated Learning ICML 2025 [PUB] [CODE]
Efficient Heterogeneity-Aware Federated Active Data Selection ICML 2025 [PUB]
Splitting with Importance-aware Updating for Heterogeneous Federated Learning with Large Language Models ICML 2025 [PUB] [CODE]
Rethinking the Temperature for Federated Heterogeneous Distillation ICML 2025 [PUB]
FedClean: A General Robust Label Noise Correction for Federated Learning ICML 2025 [PUB]
Federated Causal Structure Learning with Non-identical Variable Sets ICML 2025 [PUB]
FedECADO: A Dynamical System Model of Federated Learning ICML 2025 [PUB]
Efficient Federated Incomplete Multi-View Clustering ICML 2025 [PUB] [CODE]
Federated Incomplete Multi-view Clustering with Globally Fused Graph Guidance ICML 2025 [PUB] [CODE]
Local Pan-privacy for Federated Analytics ICML 2025 [PUB]
FedOne: Query-Efficient Federated Learning for Black-box Discrete Prompt Learning ICML 2025 [PUB] [CODE]
Hybrid Batch Normalisation: Resolving the Dilemma of Batch Normalisation in Federated Learning ICML 2025 [PUB] [CODE]
Private Federated Learning using Preference-Optimized Synthetic Data ICML 2025 [PUB] [CODE]
Enhancing Foundation Models with Federated Domain Knowledge Infusion ICML 2025 [PUB]
FedPHA: Federated Prompt Learning for Heterogeneous Client Adaptation ICML 2025 [PUB] [CODE]
Federated Oriented Learning: A Practical One-Shot Personalized Federated Learning Framework ICML 2025 [PUB] [CODE]
Federated Node-Level Clustering Network with Cross-Subgraph Link Mending ICML 2025 [PUB]
Ferret: Federated Full-Parameter Tuning at Scale for Large Language Models ICML 2025 [PUB] [CODE]
FedSSI: Rehearsal-Free Continual Federated Learning with Synergistic Synaptic Intelligence ICML 2025 [PUB]
Federated Generalised Variational Inference: A Robust Probabilistic Federated Learning Framework ICML 2025 [PUB] [CODE]
DTZO: Distributed Trilevel Zeroth Order Learning with Provable Non-Asymptotic Convergence ICML 2025 [PUB]
On-Device Collaborative Language Modeling via a Mixture of Generalists and Specialists ICML 2025 [PUB]
Safe-EF: Error Feedback for Non-smooth Constrained Optimization ICML 2025 [PUB] [CODE]
Gradient Inversion of Multimodal Models ICML 2025 [PUB] [CODE]
Widening the Network Mitigates the Impact of Data Heterogeneity on FedAvg ICML 2025 [PUB] [CODE]
Decoupled SGDA for Games with Intermittent Strategy Communication ICML 2025 [PUB]
Private Model Personalization Revisited ICML 2025 [PUB]
Leveraging Randomness in Model and Data Partitioning for Privacy Amplification ICML 2025 [PUB]
Scaffold with Stochastic Gradients: New Analysis with Linear Speed-Up ICML 2025 [PUB] [CODE]
Voronoi-grid-based Pareto Front Learning and Its Application to Collaborative Federated Learning ICML 2025 [PUB] [CODE]
FedSMU: Communication-Efficient and Generalization-Enhanced Federated Learning through Symbolic Model Updates ICML 2025 [PUB] [CODE]
One Arrow, Two Hawks: Sharpness-aware Minimization for Federated Learning via Global Model Trajectory ICML 2025 [PUB] [CODE]
Certifiably Robust Model Evaluation in Federated Learning under Meta-Distributional Shifts ICML 2025 [PUB]
Does One-shot Give the Best Shot? Mitigating Model Inconsistency in One-shot Federated Learning ICML 2025 [PUB] [CODE]
GHOST: Generalizable One-Shot Federated Graph Learning with Proxy-Based Topology Knowledge Retention ICML 2025 [PUB] [CODE]
DMM: Distributed Matrix Mechanism for Differentially-Private Federated Learning Based on Constant-Overhead Linear Secret Resharing ICML 2025 [PUB]
BSemiFL: Semi-supervised Federated Learning via a Bayesian Approach ICML 2025 [PUB]
Janus: Dual-Server Multi-Round Secure Aggregation with Verifiability for Federated Learning ICML 2025 [PUB]
EAGLES: Towards Effective, Efficient, and Economical Federated Graph Learning via Unified Sparsification ICML 2025 [PUB] [CODE]
Harnessing Heterogeneous Statistical Strength for Personalized Federated Learning via Hierarchical Bayesian Inference ICML 2025 [PUB] [CODE]
Theoretically Unmasking Inference Attacks Against LDP-Protected Clients in Federated Vision Models ICML 2025 [PUB] [CODE]
Generalization in Federated Learning: A Conditional Mutual Information Framework ICML 2025 [PUB]
The Panaceas for Improving Low-Rank Decomposition in Communication-Efficient Federated Learning ICML 2025 [PUB] [CODE]
Improved Coresets for Vertical Federated Learning: Regularized Linear and Logistic Regressions ICML 2025 [PUB] [CODE]
Privacy-Preserving Federated Convex Optimization: Balancing Partial-Participation and Efficiency via Noise Cancellation ICML 2025 [PUB]
Federated In-Context Learning: Iterative Refinement for Improved Answer Quality ICML 2025 [PUB]
SPMC: Self-Purifying Federated Backdoor Defense via Margin Contribution ICML 2025 [PUB] [CODE]
You Get What You Give: Reciprocally Fair Federated Learning ICML 2025 [PUB]
Provably Near-Optimal Federated Ensemble Distillation with Negligible Overhead ICML 2025 [PUB] [CODE]
Byzantine-Resilient Federated Alternating Gradient Descent and Minimization for Partly-Decoupled Low Rank Matrix Learning ICML 2025 [PUB]
HFIA: a parasitic feature inference attack and gradient-based defense strategy in SplitNN-based vertical federated learning Mach Learn 2025 [PUB]
Fedflow: a personalized federated learning framework for passenger flow prediction Mach Learn 2025 [PUB]
Federated causal inference from observational data Mach Learn 2025 [PUB]
TransFed: cross-domain feature alignment for semi-supervised federated transfer learning Mach Learn 2025 [PUB]
Improve global generalization for personalized federated learning within a Stackelberg game Mach Learn 2025 [PUB]
Efficient federated unlearning under plausible deniability Mach Learn 2025 [PUB] [CODE]
Energy-based Backdoor Defense Against Federated Graph Learning ICLR 2025 [PUB]
DEPT: Decoupled Embeddings for Pre-training Language Models ICLR 2025 [PUB]
Subgraph Federated Learning for Local Generalization ICLR 2025 [PUB] [CODE]
Problem-Parameter-Free Federated Learning ICLR 2025 [PUB]
Adaptive Gradient Clipping for Robust Federated Learning ICLR 2025 [PUB]
Decentralized Sporadic Federated Learning: A Unified Algorithmic Framework with Convergence Guarantees ICLR 2025 [PUB]
LoCoDL: Communication-Efficient Distributed Learning with Local Training and Compression ICLR 2025 [PUB]
Group Distributionally Robust Dataset Distillation with Risk Minimization ICLR 2025 [PUB]
GRAIN: Exact Graph Reconstruction from Gradients ICLR 2025 [PUB]
Towards Faster Decentralized Stochastic Optimization with Communication Compression ICLR 2025 [PUB]
Leveraging Variable Sparsity to Refine Pareto Stationarity in Multi-Objective Optimization ICLR 2025 [PUB]
Many-Objective Multi-Solution Transport ICLR 2025 [PUB]
Query-based Knowledge Transfer for Heterogeneous Learning Environments ICLR 2025 [PUB]
Federated Class-Incremental Learning: A Hybrid Approach Using Latent Exemplars and Data-Free Techniques to Address Local and Global Forgetting ICLR 2025 [PUB]
Federated Granger Causality Learning For Interdependent Clients With State Space Representation ICLR 2025 [PUB]
Achieving Dimension-Free Communication in Federated Learning via Zeroth-Order Optimization ICLR 2025 [PUB]
Methods with Local Steps and Random Reshuffling for Generally Smooth Non-Convex Federated Optimization ICLR 2025 [PUB]
On the Importance of Language-driven Representation Learning for Heterogeneous Federated Learning ICLR 2025 [PUB]
PRISM: Privacy-Preserving Improved Stochastic Masking for Federated Generative Models ICLR 2025 [PUB]
Differentially Private Federated Learning with Time-Adaptive Privacy Spending ICLR 2025 [PUB]
Enhancing Clustered Federated Learning: Integration of Strategies and Improved Methodologies ICLR 2025 [PUB]
Asynchronous Federated Reinforcement Learning with Policy Gradient Updates: Algorithm Design and Convergence Analysis ICLR 2025 [PUB]
On the Byzantine-Resilience of Distillation-Based Federated Learning ICLR 2025 [PUB]
Emerging Safety Attack and Defense in Federated Instruction Tuning of Large Language Models ICLR 2025 [PUB]
Event-Driven Online Vertical Federated Learning ICLR 2025 [PUB]
On the Linear Speedup of Personalized Federated Reinforcement Learning with Shared Representations ICLR 2025 [PUB]
Federated Domain Generalization with Data-free On-server Matching Gradient ICLR 2025 [PUB]
Unlocking the Potential of Model Calibration in Federated Learning ICLR 2025 [PUB]
FedLWS: Federated Learning with Adaptive Layer-wise Weight Shrinking ICLR 2025 [PUB]
Understanding the Stability-based Generalization of Personalized Federated Learning ICLR 2025 [PUB]
Federated Residual Low-Rank Adaption of Large Language Models ICLR 2025 [PUB]
FedTMOS: Efficient One-Shot Federated Learning with Tsetlin Machine ICLR 2025 [PUB]
Vertical Federated Learning with Missing Features During Training and Inference ICLR 2025 [PUB]
Federated $Q$-Learning with Reference-Advantage Decomposition: Almost Optimal Regret and Logarithmic Communication Cost ICLR 2025 [PUB]
Selective Aggregation for Low-Rank Adaptation in Federated Learning ICLR 2025 [PUB]
Privacy-Preserving Personalized Federated Prompt Learning for Multimodal Large Language Models ICLR 2025 [PUB]
Hot-pluggable Federated Learning: Bridging General and Personalized FL via Dynamic Selection ICLR 2025 [PUB]
Debiasing Federated Learning with Correlated Client Participation ICLR 2025 [PUB]
Decoupled Subgraph Federated Learning ICLR 2025 [PUB]
Bad-PFL: Exploiting Backdoor Attacks against Personalized Federated Learning ICLR 2025 [PUB]
Towards Federated RLHF with Aggregated Client Preference for LLMs ICLR 2025 [PUB]
SparsyFed: Sparse Adaptive Federated Learning ICLR 2025 [PUB]
Can Textual Gradient Work in Federated Learning? ICLR 2025 [PUB]
Mixture of Experts Made Personalized: Federated Prompt Learning for Vision-Language Models ICLR 2025 [PUB]
Enhancing Federated Domain Adaptation with Multi-Domain Prototype-Based Federated Fine-Tuning ICLR 2025 [PUB]
Connecting Federated ADMM to Bayes ICLR 2025 [PUB]
Closed-Form Merging of Parameter-Efficient Modules for Federated Continual Learning ICLR 2025 [PUB]
Federated Continual Learning Goes Online: Uncertainty-Aware Memory Management for Vision Tasks and Beyond ICLR 2025 [PUB]
Federated Few-Shot Class-Incremental Learning ICLR 2025 [PUB]
Re-Fed+: A Better Replay Strategy for Federated Incremental Learning TPAMI 2025 [PUB]
DFedADMM: Dual Constraint Controlled Model Inconsistency for Decentralize Federated Learning TPAMI 2025 [PUB]
Robust Asymmetric Heterogeneous Federated Learning With Corrupted Clients TPAMI 2025 [PUB]
Federated Multi-View K-Means Clustering TPAMI 2025 [PUB]
Stabilizing and Accelerating Federated Learning on Heterogeneous Data With Partial Client Participation TPAMI 2025 [PUB]
Medical Federated Model With Mixture of Personalized and Shared Components TPAMI 2025 [PUB]
FedAST: Federated Asynchronous Simultaneous Training UAI 2024 [PUB]
On Convergence of Federated Averaging Langevin Dynamics UAI 2024 [PUB]
On the Convergence of Hierarchical Federated Learning with Partial Worker Participation UAI 2024 [PUB]
Pure Exploration in Asynchronous Federated Bandits UAI 2024 [PUB]
One-shot Federated Learning via Synthetic Distiller-Distillate Communication NeurIPS 2024 [PUB]
Nonconvex Federated Learning on Compact Smooth Submanifolds With Heterogeneous Data NeurIPS 2024 [PUB]
FedGMKD: An Efficient Prototype Federated Learning Framework through Knowledge Distillation and Discrepancy-Aware Aggregation NeurIPS 2024 [PUB]
Improving Generalization in Federated Learning with Model-Data Mutual Information Regularization: A Posterior Inference Approach NeurIPS 2024 [PUB]
Federated Model Heterogeneous Matryoshka Representation Learning NeurIPS 2024 [PUB]
Federated Graph Learning for Cross-Domain Recommendation NeurIPS 2024 [PUB]
FedGMark: Certifiably Robust Watermarking for Federated Graph Learning NeurIPS 2024 [PUB]
Dual-Personalizing Adapter for Federated Foundation Models NeurIPS 2024 [PUB]
Federated Natural Policy Gradient and Actor Critic Methods for Multi-task Reinforcement Learning NeurIPS 2024 [PUB]
Taming the Long Tail in Human Mobility Prediction NeurIPS 2024 [PUB]
Dual Defense: Enhancing Privacy and Mitigating Poisoning Attacks in Federated Learning NeurIPS 2024 [PUB]
Graph-enhanced Optimizers for Structure-aware Recommendation Embedding Evolution NeurIPS 2024 [PUB]
DoFIT: Domain-aware Federated Instruction Tuning with Alleviated Catastrophic Forgetting NeurIPS 2024 [PUB]
Efficient Federated Learning against Heterogeneous and Non-stationary Client Unavailability NeurIPS 2024 [PUB]
Federated Transformer: Multi-Party Vertical Federated Learning on Practical Fuzzily Linked Data NeurIPS 2024 [PUB]
FIARSE: Model-Heterogeneous Federated Learning via Importance-Aware Submodel Extraction NeurIPS 2024 [PUB]
Probabilistic Federated Prompt-Tuning with Non-IID and Imbalanced Data NeurIPS 2024 [PUB]
FLoRA: Federated Fine-Tuning Large Language Models with Heterogeneous Low-Rank Adaptations NeurIPS 2024 [PUB]
Taming Cross-Domain Representation Variance in Federated Prototype Learning with Heterogeneous Data Domains NeurIPS 2024 [PUB]
pFedClub: Controllable Heterogeneous Model Aggregation for Personalized Federated Learning NeurIPS 2024 [PUB]
Why Go Full? Elevating Federated Learning Through Partial Network Updates NeurIPS 2024 [PUB]
FuseFL: One-Shot Federated Learning through the Lens of Causality with Progressive Model Fusion NeurIPS 2024 [PUB]
FedSSP: Federated Graph Learning with Spectral Knowledge and Personalized Preference NeurIPS 2024 [PUB]
Handling Learnwares from Heterogeneous Feature Spaces with Explicit Label Exploitation NeurIPS 2024 [PUB]
A-FedPD: Aligning Dual-Drift is All Federated Primal-Dual Learning Needs NeurIPS 2024 [PUB]
Private and Personalized Frequency Estimation in a Federated Setting NeurIPS 2024 [PUB]
The Sample-Communication Complexity Trade-off in Federated Q-Learning NeurIPS 2024 [PUB]
Federated Ensemble-Directed Offline Reinforcement Learning NeurIPS 2024 [PUB]
Federated Black-Box Adaptation for Semantic Segmentation NeurIPS 2024 [PUB]
Thinking Forward: Memory-Efficient Federated Finetuning of Language Models NeurIPS 2024 [PUB]
Federated Learning from Vision-Language Foundation Models: Theoretical Analysis and Method NeurIPS 2024 [PUB]
Optimal Design for Human Preference Elicitation NeurIPS 2024 [PUB]
Towards Diverse Device Heterogeneous Federated Learning via Task Arithmetic Knowledge Integration NeurIPS 2024 [PUB]
Personalized Federated Learning via Feature Distribution Adaptation NeurIPS 2024 [PUB]
SCAFFLSA: Taming Heterogeneity in Federated Linear Stochastic Approximation and TD Learning NeurIPS 2024 [PUB]
A Bayesian Approach for Personalized Federated Learning in Heterogeneous Settings NeurIPS 2024 [PUB]
RFLPA: A Robust Federated Learning Framework against Poisoning Attacks with Secure Aggregation NeurIPS 2024 [PUB]
FedGTST: Boosting Global Transferability of Federated Models via Statistics Tuning NeurIPS 2024 [PUB]
End-to-end Learnable Clustering for Intent Learning in Recommendation NeurIPS 2024 [PUB]
FedLPA: One-shot Federated Learning with Layer-Wise Posterior Aggregation NeurIPS 2024 [PUB]
Time-FFM: Towards LM-Empowered Federated Foundation Model for Time Series Forecasting NeurIPS 2024 [PUB]
FOOGD: Federated Collaboration for Both Out-of-distribution Generalization and Detection NeurIPS 2024 [PUB]
A Swiss Army Knife for Heterogeneous Federated Learning: Flexible Coupling via Trace Norm NeurIPS 2024 [PUB]
FedNE: Surrogate-Assisted Federated Neighbor Embedding for Dimensionality Reduction NeurIPS 2024 [PUB]
Low Precision Local Training is Enough for Federated Learning NeurIPS 2024 [PUB]
Resource-Aware Federated Self-Supervised Learning with Global Class Representations NeurIPS 2024 [PUB]
On the Necessity of Collaboration for Online Model Selection with Decentralized Data NeurIPS 2024 [PUB]
The Power of Extrapolation in Federated Learning NeurIPS 2024 [PUB]
(FL)$^2$: Overcoming Few Labels in Federated Semi-Supervised Learning NeurIPS 2024 [PUB]
On Sampling Strategies for Spectral Model Sharding NeurIPS 2024 [PUB]
Customizing Language Models with Instance-wise LoRA for Sequential Recommendation NeurIPS 2024 [PUB]
SpaFL: Communication-Efficient Federated Learning With Sparse Models And Low Computational Overhead NeurIPS 2024 [PUB]
HYDRA-FL: Hybrid Knowledge Distillation for Robust and Accurate Federated Learning NeurIPS 2024 [PUB]
Stabilized Proximal-Point Methods for Federated Optimization NeurIPS 2024 [PUB]
DapperFL: Domain Adaptive Federated Learning with Model Fusion Pruning for Edge Devices NeurIPS 2024 [PUB]
Parameter Disparities Dissection for Backdoor Defense in Heterogeneous Federated Learning NeurIPS 2024 [PUB]
Does Worst-Performing Agent Lead the Pack? Analyzing Agent Dynamics in Unified Distributed SGD NeurIPS 2024 [PUB]
FedAvP: Augment Local Data via Shared Policy in Federated Learning NeurIPS 2024 [PUB]
CoBo: Collaborative Learning via Bilevel Optimization NeurIPS 2024 [PUB]
Convergence Analysis of Split Federated Learning on Heterogeneous Data NeurIPS 2024 [PUB]
Communication-Efficient Federated Group Distributionally Robust Optimization NeurIPS 2024 [PUB]
Ferrari: Federated Feature Unlearning via Optimizing Feature Sensitivity NeurIPS 2024 [PUB]
Federated Learning over Connected Modes NeurIPS 2024 [PUB]
Personalized Federated Learning with Mixture of Models for Adaptive Prediction and Model Fine-Tuning NeurIPS 2024 [PUB]
Does Egalitarian Fairness Lead to Instability? The Fairness Bounds in Stable Federated Learning Under Altruistic Behaviors NeurIPS 2024 [PUB]
Federated Online Prediction from Experts with Differential Privacy: Separations and Regret Speed-ups NeurIPS 2024 [PUB]
DataStealing: Steal Data from Diffusion Models in Federated Learning with Multiple Trojans NeurIPS 2024 [PUB]
Federated Behavioural Planes: Explaining the Evolution of Client Behaviour in Federated Learning NeurIPS 2024 [PUB]
Hierarchical Federated Learning with Multi-Timescale Gradient Correction NeurIPS 2024 [PUB]
HyperPrism: An Adaptive Non-linear Aggregation Framework for Distributed Machine Learning over Non-IID Data and Time-varying Communication Links NeurIPS 2024 [PUB]
SPEAR: Exact Gradient Inversion of Batches in Federated Learning NeurIPS 2024 [PUB]
Federated Learning under Periodic Client Participation and Heterogeneous Data: A New Communication-Efficient Algorithm and Analysis NeurIPS 2024 [PUB]
Bridging Gaps: Federated Multi-View Clustering in Heterogeneous Hybrid Views NeurIPS 2024 [PUB]
Confusion-Resistant Federated Learning via Diffusion-Based Data Harmonization on Non-IID Data NeurIPS 2024 [PUB]
Local Superior Soups: A Catalyst for Model Merging in Cross-Silo Federated Learning NeurIPS 2024 [PUB]
Free-Rider and Conflict Aware Collaboration Formation for Cross-Silo Federated Learning NeurIPS 2024 [PUB]
Classifier Clustering and Feature Alignment for Federated Learning under Distributed Concept Drift NeurIPS 2024 [PUB]
Heterogeneity-Guided Client Sampling: Towards Fast and Efficient Non-IID Federated Learning NeurIPS 2024 [PUB]
FACT or Fiction: Can Truthful Mechanisms Eliminate Federated Free Riding? NeurIPS 2024 [PUB]
Active preference learning for ordering items in- and out-of-sample NeurIPS 2024 [PUB]
Federated Fine-tuning of Large Language Models under Heterogeneous Tasks and Client Resources NeurIPS 2024 [PUB]
Fine-Tuning Personalization in Federated Learning to Mitigate Adversarial Clients NeurIPS 2024 [PUB]
Revisiting Ensembling in One-Shot Federated Learning NeurIPS 2024 [PUB]
FedLLM-Bench: Realistic Benchmarks for Federated Learning of Large Language Models NeurIPS 2024 [PUB]
$ exttt{pfl-research}$: simulation framework for accelerating research in Private Federated Learning NeurIPS 2024 [PUB]
FEDMEKI: A Benchmark for Scaling Medical Foundation Models via Federated Knowledge Injection NeurIPS 2024 [PUB]
Momentum Approximation in Asynchronous Private Federated Learning NeurIPS workshop 2024 [PUB]
Cohort Squeeze: Beyond a Single Communication Round per Cohort in Cross-Device Federated Learning NeurIPS workshop 2024 [PUB]
Federated Learning with Generative Content NeurIPS workshop 2024 [PUB]
Leveraging Unstructured Text Data for Federated Instruction Tuning of Large Language Models NeurIPS workshop 2024 [PUB]
Emerging Safety Attack and Defense in Federated Instruction Tuning of Large Language Models NeurIPS workshop 2024 [PUB]
Defection-Free Collaboration between Competitors in a Learning System NeurIPS workshop 2024 [PUB]
On the Convergence Rates of Federated Q-Learning across Heterogeneous Environments NeurIPS workshop 2024 [PUB]
EncCluster: Bringing Functional Encryption in Federated Foundational Models NeurIPS workshop 2024 [PUB]
Ferret: Federated Full-Parameter Tuning at Scale for Large Language Models NeurIPS workshop 2024 [PUB]
Hot Pluggable Federated Learning NeurIPS workshop 2024 [PUB]
Federated Dynamical Low-Rank Training with Global Loss Convergence Guarantees NeurIPS workshop 2024 [PUB]
The Future of Large Language Model Pre-training is Federated NeurIPS workshop 2024 [PUB]
Collaborative Learning with Shared Linear Representations: Statistical Rates and Optimal Algorithms NeurIPS workshop 2024 [PUB]
The SynapticCity Phenomenon: When All Foundation Models Marry Federated Learning and Blockchain NeurIPS workshop 2024 [PUB]
ZOOPFL: Exploring Black-box Foundation Models for Personalized Federated Learning NeurIPS workshop 2024 [PUB]
DeComFL: Federated Learning with Dimension-Free Communication NeurIPS workshop 2024 [PUB]
Improving Group Connectivity for Generalization of Federated Deep Learning NeurIPS workshop 2024 [PUB]
MAP: Model Merging with Amortized Pareto Front Using Limited Computation NeurIPS workshop 2024 [PUB]
OPA: One-shot Private Aggregation with Single Client Interaction and its Applications to Federated Learning NeurIPS workshop 2024 [PUB]
Adaptive Hybrid Model Pruning in Federated Learning through Loss Exploration NeurIPS workshop 2024 [PUB]
Worldwide Federated Training of Language Models NeurIPS workshop 2024 [PUB]
FedStein: Enhancing Multi-Domain Federated Learning Through James-Stein Estimator NeurIPS workshop 2024 [PUB]
Enhancing Causal Discovery in Federated Settings with Limited Local Samples NeurIPS workshop 2024 [PUB]
$ exttt{pfl-research}$: simulation framework for accelerating research in Private Federated Learning NeurIPS workshop 2024 [PUB]
DMM: Distributed Matrix Mechanism for Differentially-Private Federated Learning using Packed Secret Sharing NeurIPS workshop 2024 [PUB]
FedCBO: Reaching Group Consensus in Clustered Federated Learning through Consensus-based Optimization JMLR 2024 [PUB]
Effective Federated Graph Matching ICML 2024 [PUB]
Understanding Server-Assisted Federated Learning in the Presence of Incomplete Client Participation ICML 2024 [PUB]
Beyond the Federation: Topology-aware Federated Learning for Generalization to Unseen Clients ICML 2024 [PUB]
FedBPT: Efficient Federated Black-box Prompt Tuning for Large Language Models ICML 2024 [PUB]
Bridging Model Heterogeneity in Federated Learning via Uncertainty-based Asymmetrical Reciprocity Learning ICML 2024 [PUB]
A New Theoretical Perspective on Data Heterogeneity in Federated Optimization ICML 2024 [PUB]
Enhancing Storage and Computational Efficiency in Federated Multimodal Learning for Large-Scale Models ICML 2024 []
Momentum for the Win: Collaborative Federated Reinforcement Learning across Heterogeneous Environments ICML 2024 [PUB]
Byzantine-Robust Federated Learning: Impact of Client Subsampling and Local Updates ICML 2024 [PUB]
Provable Benefits of Local Steps in Heterogeneous Federated Learning for Neural Networks: A Feature Learning Perspective ICML 2024 [PUB]
Accelerating Federated Learning with Quick Distributed Mean Estimation ICML 2024 [PUB]
Fair Federated Learning via the Proportional Veto Core ICML 2024 [PUB]
AegisFL: Efficient and Flexible Privacy-Preserving Byzantine-Robust Cross-silo Federated Learning ICML 2024 [PUB]
Recovering Labels from Local Updates in Federated Learning ICML 2024 [PUB]
FedMBridge: Bridgeable Multimodal Federated Learning ICML 2024 [PUB]
Harmonizing Generalization and Personalization in Federated Prompt Learning ICML 2024 [PUB]
Locally Estimated Global Perturbations are Better than Local Perturbations for Federated Sharpness-aware Minimization ICML 2024 [PUB]
Accelerating Heterogeneous Federated Learning with Closed-form Classifiers ICML 2024 [PUB]
Federated Combinatorial Multi-Agent Multi-Armed Bandits ICML 2024 [PUB]
A Doubly Recursive Stochastic Compositional Gradient Descent Method for Federated Multi-Level Compositional Optimization ICML 2024 [PUB]
Private Heterogeneous Federated Learning Without a Trusted Server Revisited: Error-Optimal and Communication-Efficient Algorithms for Convex Losses ICML 2024 [PUB]
FedRC: Tackling Diverse Distribution Shifts Challenge in Federated Learning by Robust Clustering ICML 2024 [PUB]
Pursuing Overall Welfare in Federated Learning through Sequential Decision Making ICML 2024 [PUB]
PrE-Text: Training Language Models on Private Federated Data in the Age of LLMs ICML 2024 [PUB]
Self-Driven Entropy Aggregation for Byzantine-Robust Heterogeneous Federated Learning ICML 2024 [PUB]
Overcoming Data and Model heterogeneities in Decentralized Federated Learning via Synthetic Anchors ICML 2024 [PUB]
Federated Optimization with Doubly Regularized Drift Correction ICML 2024 [PUB]
FedSC: Provable Federated Self-supervised Learning with Spectral Contrastive Objective over Non-i.i.d. Data ICML 2024 [PUB]
Certifiably Byzantine-Robust Federated Conformal Prediction ICML 2024 [PUB]
Achieving Lossless Gradient Sparsification via Mapping to Alternative Space in Federated Learning ICML 2024 [PUB]
Clustered Federated Learning via Gradient-based Partitioning ICML 2024 [PUB]
Recurrent Early Exits for Federated Learning with Heterogeneous Clients ICML 2024 [PUB]
Rethinking the Flat Minima Searching in Federated Learning ICML 2024 [PUB]
FedBAT: Communication-Efficient Federated Learning via Learnable Binarization ICML 2024 [PUB]
Federated Representation Learning in the Under-Parameterized Regime ICML 2024 [PUB]
FedLMT: Tackling System Heterogeneity of Federated Learning via Low-Rank Model Training with Theoretical Guarantees ICML 2024 [PUB]
Noise-Aware Algorithm for Heterogeneous Differentially Private Federated Learning ICML 2024 [PUB]
SILVER: Single-loop variance reduction and application to federated learning ICML 2024 [PUB]
SignSGD with Federated Defense: Harnessing Adversarial Attacks through Gradient Sign Decoding ICML 2024 [PUB]
FedCal: Achieving Local and Global Calibration in Federated Learning via Aggregated Parameterized Scaler ICML 2024 [PUB]
Federated Continual Learning via Prompt-based Dual Knowledge Transfer ICML 2024 [PUB]
Federated Full-Parameter Tuning of Billion-Sized Language Models with Communication Cost under 18 Kilobytes ICML 2024 [PUB]
Decomposable Submodular Maximization in Federated Setting ICML 2024 [PUB]
Private and Federated Stochastic Convex Optimization: Efficient Strategies for Centralized Systems ICML 2024 [PUB]
Improved Modelling of Federated Datasets using Mixtures-of-Dirichlet-Multinomials ICML 2024 [PUB]
Lessons from Generalization Error Analysis of Federated Learning: You May Communicate Less Often! ICML 2024 [PUB]
Byzantine Resilient and Fast Federated Few-Shot Learning ICML 2024 [PUB]
Causally Motivated Personalized Federated Invariant Learning with Shortcut-Averse Information-Theoretic Regularization ICML 2024 [PUB]
Ranking-based Client Imitation Selection for Efficient Federated Learning ICML 2024 [PUB]
Towards the Theory of Unsupervised Federated Learning: Non-asymptotic Analysis of Federated EM Algorithms ICML 2024 [PUB]
FADAS: Towards Federated Adaptive Asynchronous Optimization ICML 2024 [PUB]
Federated Offline Reinforcement Learning: Collaborative Single-Policy Coverage Suffices ICML 2024 [PUB]
FedREDefense: Defending against Model Poisoning Attacks for Federated Learning using Model Update Reconstruction Error ICML 2024 [PUB]
MH-pFLID: Model Heterogeneous personalized Federated Learning via Injection and Distillation for Medical Data Analysis ICML 2024 [PUB]
Federated Neuro-Symbolic Learning ICML 2024 [PUB]
Adaptive Group Personalization for Federated Mutual Transfer Learning ICML 2024 [PUB]
Balancing Similarity and Complementarity for Federated Learning ICML 2024 [PUB]
Federated Self-Explaining GNNs with Anti-shortcut Augmentations ICML 2024 [PUB]
A Federated Stochastic Multi-level Compositional Minimax Algorithm for Deep AUC Maximization ICML 2024 [PUB]
COALA: A Practical and Vision-Centric Federated Learning Platform ICML 2024 [PUB]
Secure and fast asynchronous Vertical Federated Learning via cascaded hybrid optimization Mach Learn 2024 [PUB]
Communication-efficient clustered federated learning via model distance USTC; State Key Laboratory of Cognitive Intelligence Mach Learn 2024 [PUB]
Federated learning with superquantile aggregation for heterogeneous data. Google Research Mach Learn 2024 [PUB] [PDF] [CODE]
Aligning model outputs for class imbalanced non-IID federated learning NJU Mach Learn 2024 [PUB]
Federated Learning of Generalized Linear Causal Networks TPAMI 2024 [PUB]
Cross-Modal Federated Human Activity Recognition TPAMI 2024 [PUB]
Federated Gaussian Process: Convergence, Automatic Personalization and Multi-Fidelity Modeling Northeastern University; UoM TPAMI 2024 [PUB] [PDF] [CODE]
The Impact of Adversarial Attacks on Federated Learning: A Survey IIT TPAMI 2024 [PUB]
Understanding and Mitigating Dimensional Collapse in Federated Learning NUS TPAMI 2024 [PUB] [PDF] [CODE]
No One Left Behind: Real-World Federated Class-Incremental Learning CAS; UCAS TPAMI 2024 [PUB] [PDF] [CODE]
Generalizable Heterogeneous Federated Cross-Correlation and Instance Similarity Learning WHU TPAMI 2024 [PUB] [PDF] [CODE]
Multi-Stage Asynchronous Federated Learning With Adaptive Differential Privacy HPU; XJTU TPAMI 2024 [PUB] [PDF] [CODE]
A Bayesian Federated Learning Framework With Online Laplace Approximation SUSTech TPAMI 2024 [PUB] [PDF] [CODE]
Enhancing One-Shot Federated Learning Through Data and Ensemble Co-Boosting USTC; HKBU ICLR 2024 [PUB]
One-shot Empirical Privacy Estimation for Federated Learning Google ICLR 2024 [PUB] [PDF]
Stochastic Controlled Averaging for Federated Learning with Communication Compression LinkedIn; UPenn ICLR 2024 [PUB] [PDF]
A Lightweight Method for Tackling Unknown Participation Statistics in Federated Averaging IBM ICLR 2024 [PUB] [PDF] [CODE]
A Mutual Information Perspective on Federated Contrastive Learning QualComm ICLR 2024 [PUB]
Benchmarking Algorithms for Federated Domain Generalization Purdue University ICLR 2024 [PUB] [PDF] [CODE]
Effective and Efficient Federated Tree Learning on Hybrid Data UC Berkeley ICLR 2024 [PUB] [PDF]
Federated Recommendation with Additive Personalization UTS ICLR 2024 [PUB] [PDF] [CODE]
Tackling the Data Heterogeneity in Asynchronous Federated Learning with Cached Update Calibration PSU ICLR 2024 [PUB] [SUPP]
Federated Orthogonal Training: Mitigating Global Catastrophic Forgetting in Continual Federated Learning USC ICLR 2024 [PUB] [SUPP] [PDF]
Accurate Forgetting for Heterogeneous Federated Continual Learning THU ICLR 2024 [PUB] [CODE]
Federated Causal Discovery from Heterogeneous Data MBZUAI ICLR 2024 [PUB] [PDF] [CODE]
On Differentially Private Federated Linear Contextual Bandits Wayne State University ICLR 2024 [PUB] [SUPP] [PDF]
Incentivized Truthful Communication for Federated Bandits University of Virginia ICLR 2024 [PUB] [PDF]
Principled Federated Domain Adaptation: Gradient Projection and Auto-Weighting UIUC ICLR 2024 [PUB]
FedP3: Federated Personalized and Privacy-friendly Network Pruning under Model Heterogeneity KAUST ICLR 2024 [PUB]
Text-driven Prompt Generation for Vision-Language Models in Federated Learning Robert Bosch LLC ICLR 2024 [PUB] [PDF]
Improving LoRA in Privacy-preserving Federated Learning Northeastern University ICLR 2024 [PUB]
FedWon: Triumphing Multi-domain Federated Learning Without Normalization Sony AI ICLR 2024 [PUB] [PDF]
FedTrans: Client-Transparent Utility Estimation for Robust Federated Learning TU Delft ICLR 2024 [PUB]
FedCompass: Efficient Cross-Silo Federated Learning on Heterogeneous Client Devices Using a Computing Power-Aware Scheduler ANL; UIUC; NCSA ICLR 2024 [PUB] [PDF] [CODE] [PAGE]
Bayesian Coreset Optimization for Personalized Federated Learning IIT Bombay ICLR 2024 [PUB]
Layer-wise linear mode connectivity Ruhr-Universtät Bochum ICLR 2024 [PUB] [PDF] [SUPP]
Fake It Till Make It: Federated Learning with Consensus-Oriented Generation SJTU ICLR 2024 [PUB] [PDF]
Hiding in Plain Sight: Disguising Data Stealing Attacks in Federated Learning INSAIT ICLR 2024 [PUB] [SUPP] [PDF]
Finite-Time Analysis of On-Policy Heterogeneous Federated Reinforcement Learning Columbia University ICLR 2024 [PUB] [PDF]
Adaptive Federated Learning with Auto-Tuned Clients Rice University ICLR 2024 [PUB] [SUPP] [PDF]
Backdoor Federated Learning by Poisoning Backdoor-Critical Layers ND ICLR 2024 [PUB] [SUPP] [PDF]
Federated Q-Learning: Linear Regret Speedup with Low Communication Cost PSU ICLR 2024 [PUB] [SUPP] [PDF]
FedImpro: Measuring and Improving Client Update in Federated Learning HKBU ICLR 2024 [PUB] [PDF]
Federated Wasserstein Distance MIT ICLR 2024 [PUB] [SUPP] [PDF]
An improved analysis of per-sample and per-update clipping in federated learning DTU ICLR 2024 [PUB]
FedCDA: Federated Learning with Cross-rounds Divergence-aware Aggregation NTU ICLR 2024 [PUB] [SUPP]
Internal Cross-layer Gradients for Extending Homogeneity to Heterogeneity in Federated Learning HKU ICLR 2024 [PUB] [PDF]
Momentum Benefits Non-iid Federated Learning Simply and Provably PKU; UPenn ICLR 2024 [PUB] [PDF]
Communication-Efficient Federated Non-Linear Bandit Optimization Yale University ICLR 2024 [PUB] [PDF]
Fair and Efficient Contribution Valuation for Vertical Federated Learning Huawei ICLR 2024 [PUB] [SUPP] [PDF] [CODE]
Demystifying Local & Global Fairness Trade-offs in Federated Learning Using Partial Information Decomposition UMCP ICLR 2024 [PUB] [PDF]
Learning Personalized Causally Invariant Representations for Heterogeneous Federated Clients PolyU ICLR 2024 [PUB]
PeFLL: Personalized Federated Learning by Learning to Learn IST ICLR 2024 [PUB] [SUPP] [PDF]
Communication-Efficient Gradient Descent-Accent Methods for Distributed Variational Inequalities: Unified Analysis and Local Updates JHU ICLR 2024 [PUB] [SUPP] [PDF]
FedInverse: Evaluating Privacy Leakage in Federated Learning USQ ICLR 2024 [PUB] [SUPP]
FedDA: Faster Adaptive Gradient Methods for Federated Constrained Optimization UMCP ICLR 2024 [PUB] [SUPP] [PDF]
Robust Training of Federated Models with Extremely Label Deficiency HKBU ICLR 2024 [PUB] [PDF] [CODE]
Understanding Convergence and Generalization in Federated Learning through Feature Learning Theory RIKEN AIP ICLR 2024 [PUB]
Teach LLMs to Phish: Stealing Private Information from Language Models Princeton University ICLR 2024 [PUB]
Like Oil and Water: Group Robustness Methods and Poisoning Defenses Don't Mix UMCP ICLR 2024 [PUB]
Accelerated Convergence of Stochastic Heavy Ball Method under Anisotropic Gradient Noise HKUST ICLR 2024 [PUB] [PDF]
Towards Eliminating Hard Label Constraints in Gradient Inversion Attacks CAS ICLR 2024 [PUB] [SUPP] [PDF] [CODE]
Local Composite Saddle Point Optimization Purdue University ICLR 2024 [PUB] [PDF]
Enhancing Neural Training via a Correlated Dynamics Model TIIT ICLR 2024 [PUB] [PDF]
EControl: Fast Distributed Optimization with Compression and Error Control Saarland University ICLR 2024 [PUB] [SUPP] [PDF]
Constructing Adversarial Examples for Vertical Federated Learning: Optimal Client Corruption through Multi-Armed Bandit HKUST ICLR 2024 [PUB]
FedHyper: A Universal and Robust Learning Rate Scheduler for Federated Learning with Hypergradient Descent UMCP ICLR 2024 [PUB] [SUPP] [PDF] [CODE]
Heterogeneous Personalized Federated Learning by Local-Global Updates Mixing via Convergence Rate CUHK ICLR 2024 [PUB]
Breaking Physical and Linguistic Borders: Multilingual Federated Prompt Tuning for Low-Resource Languages University of Cambridge ICLR 2024 [PUB]
Simple Minimax Optimal Byzantine Robust Algorithm for Nonconvex Objectives with Uniform Gradient Heterogeneity NTT DATA Mathematical Systems Inc. ICLR 2024 [PUB]
VFLAIR: A Research Library and Benchmark for Vertical Federated Learning THU ICLR 2024 [PUB] [PDF] [CODE]
Incentive-Aware Federated Learning with Training-Time Model Rewards NUS ICLR 2024 [PUB] [SUPP]
VertiBench: Advancing Feature Distribution Diversity in Vertical Federated Learning Benchmarks NUS ICLR 2024 [PUB] [PDF] [CODE]
FedLoGe: Joint Local and Generic Federated Learning under Long-tailed Data ZJU ICLR 2024 [PUB] [SUPP] [PDF]
SimFBO: Towards Simple, Flexible and Communication-efficient Federated Bilevel Learning University at Buffalo NeurIPS 2023 [PUB] [PDF] [SUPP]
Mechanism Design for Collaborative Normal Mean Estimation UW-Madison NeurIPS 2023 [PUB] [PDF]
Robust Distributed Learning: Tight Error Bounds and Breakdown Point under Data Heterogeneity EPFL NeurIPS 2023 [PUB] [PDF] [CODE]
Incentives in Federated Learning: Equilibria, Dynamics, and Mechanisms for Welfare Maximization UIUC NeurIPS 2023 [PUB] [SUPP]
Convergence Analysis of Sequential Federated Learning on Heterogeneous Data BUPT NeurIPS 2023 [PUB] [PDF] [CODE]
Handling Data Heterogeneity via Architectural Design for Federated Visual Recognition MBZUAI NeurIPS 2023 [PUB] [PDF] [CODE]
Private Federated Frequency Estimation: Adapting to the Hardness of the Instance JHU NeurIPS 2023 [PUB] [SUPP] [PDF]
Zeroth-Order Methods for Nondifferentiable, Nonconvex, and Hierarchical Federated Optimization Rutgers University NeurIPS 2023 [PUB] [SUPP] [PDF]
Incentivized Communication for Federated Bandits University of Virginia NeurIPS 2023 [PUB] [PDF]
Multiply Robust Federated Estimation of Targeted Average Treatment Effects Northeastern University NeurIPS 2023 [PUB] [PDF]
IBA: Towards Irreversible Backdoor Attacks in Federated Learning Vanderbilt University; VinUniversity NeurIPS 2023 [PUB] [SUPP] [CODE]
EvoFed: Leveraging Evolutionary Strategies for Communication-Efficient Federated Learning KAIST NeurIPS 2023 [PUB] [SUPP] [PDF]
Federated Linear Bandits with Finite Adversarial Actions University of Virginia NeurIPS 2023 [PUB] [SUPP] [PDF]
FedNAR: Federated Optimization with Normalized Annealing Regularization MBZUAI NeurIPS 2023 [PUB] [SUPP] [PDF] [CODE]
Guiding The Last Layer in Federated Learning with Pre-Trained Models Concordia University NeurIPS 2023 [PUB] [SUPP] [PDF] [CODE]
Fine-Grained Theoretical Analysis of Federated Zeroth-Order Optimization HZAU NeurIPS 2023 [PUB] [SUPP]
Navigating Data Heterogeneity in Federated Learning: A Semi-Supervised Approach for Object Detection KAIST NeurIPS 2023 [PUB] [SUPP] [PDF] [CODE]
A Data-Free Approach to Mitigate Catastrophic Forgetting in Federated Class Incremental Learning for Vision Tasks USC NeurIPS 2023 [PUB] [PDF] [CODE]
Is Heterogeneity Notorious? Taming Heterogeneity to Handle Test-Time Shift in Federated Learning UTS NeurIPS 2023 [PUB] [SUPP]
One-Pass Distribution Sketch for Measuring Data Heterogeneity in Federated Learning Rice University NeurIPS 2023 [PUB] [SUPP] [CODE]
Lockdown: Backdoor Defense for Federated Learning with Isolated Subspace Training Gatech NeurIPS 2023 [PUB] [SUPP] [CODE]
FedGame: A Game-Theoretic Defense against Backdoor Attacks in Federated Learning PSU; UIUC NeurIPS 2023 [PUB] [SUPP] [CODE]
Towards Personalized Federated Learning via Heterogeneous Model Reassembly PSU NeurIPS 2023 [PUB] [SUPP] [PDF] [CODE]
Every Parameter Matters: Ensuring the Convergence of Federated Learning with Dynamic Heterogeneous Models Reduction GWU NeurIPS 2023 [PUB] [SUPP] [PDF]
DFRD: Data-Free Robustness Distillation for Heterogeneous Federated Learning ECNU NeurIPS 2023 [PUB] [SUPP] [PDF] [CODE]
A Unified Solution for Privacy and Communication Efficiency in Vertical Federated Learning Western University NeurIPS 2023 [PUB] [SUPP] [CODE]
RECESS Vaccine for Federated Learning: Proactive Defense Against Model Poisoning Attacks Xidian University; University of Guelph; Zhejiang Key Laboratory of Multi-dimensional Perception Technology, Application and Cybersecurity NeurIPS 2023 [PUB] [SUPP] [PDF]
Federated Learning with Bilateral Curation for Partially Class-Disjoint Data SJTU; Shanghai AI Laboratory NeurIPS 2023 [PUB] [SUPP] [CODE]
Federated Learning with Client Subsampling, Data Heterogeneity, and Unbounded Smoothness: A New Algorithm and Lower Bounds GMU; SJTU NeurIPS 2023 [PUB] [SUPP] [CODE]
FedL2P: Federated Learning to Personalize University of Cambridge; Samsung AI Center NeurIPS 2023 [PUB] [SUPP] [PDF] [CODE]
Adaptive Test-Time Personalization for Federated Learning UIUC NeurIPS 2023 [PUB] [PDF] [CODE]
Federated Conditional Stochastic Optimization University of Pittsburgh NeurIPS 2023 [PUB] [SUPP] [PDF] [CODE]
Federated Spectral Clustering via Secure Similarity Reconstruction CUHK NeurIPS 2023 [PUB]
Mobilizing Personalized Federated Learning in Infrastructure-Less and Heterogeneous Environments via Random Walk Stochastic ADMM UM-Dearborn NeurIPS 2023 [PUB] [SUPP] [PDF]
FedGCN: Convergence-Communication Tradeoffs in Federated Training of Graph Convolutional Networks CMU NeurIPS 2023 [PUB] [SUPP] [PDF] [CODE]
Federated Multi-Objective Learning RIT NeurIPS 2023 [PUB] [SUPP] [PDF]
FLuID: Mitigating Stragglers in Federated Learning using Invariant Dropout University of British Columbia; Gatech NeurIPS 2023 [PUB] [SUPP] [PDF] [CODE]
Resolving the Tug-of-War: A Separation of Communication and Learning in Federated Learning University of Pittsburgh NeurIPS 2023 [PUB] [SUPP]
Communication-Efficient Federated Bilevel Optimization with Global and Local Lower Level Problems University of Pittsburgh NeurIPS 2023 [PUB] [SUPP] [PDF]
StableFDG: Style and Attention Based Learning for Federated Domain Generalization KAIST; Purdue University NeurIPS 2023 [PUB] [PDF]
Understanding How Consistency Works in Federated Learning via Stage-wise Relaxed Initialization The University of Sydney NeurIPS 2023 [PUB] [SUPP] [PDF]
DELTA: Diverse Client Sampling for Fasting Federated Learning CUHK; The Shenzhen Institute of Artificial Intelligence and Robotics for Society NeurIPS 2023 [PUB] [SUPP] [PDF]
Federated Compositional Deep AUC Maximization Temple University NeurIPS 2023 [PUB] [SUPP] [PDF]
A3FL: Adversarially Adaptive Backdoor Attacks to Federated Learning PSU NeurIPS 2023 [PUB] [SUPP] [CODE]
Flow: Per-instance Personalized Federated Learning University of Massachusetts NeurIPS 2023 [PUB] [SUPP] [PDF] [CODE]
Eliminating Domain Bias for Federated Learning in Representation Space SJTU NeurIPS 2023 [PUB] [SUPP] [PDF] [CODE]
Federated Learning with Manifold Regularization and Normalized Update Reaggregation BIT NeurIPS 2023 [PUB] [SUPP] [PDF]
Structured Federated Learning through Clustered Additive Modeling University of Technology Sydney NeurIPS 2023 [PUB] [SUPP]
Fed-GraB: Federated Long-tailed Learning with Self-Adjusting Gradient Balancer ZJU; Singapore University of Technology and Design NeurIPS 2023 [PUB] [SUPP] [PDF] [CODE]
Dynamic Personalized Federated Learning with Adaptive Differential Privacy WHU NeurIPS 2023 [PUB] [SUPP] [CODE]
Fed-CO$_{2}$ : Cooperation of Online and Offline Models for Severe Data Heterogeneity in Federated Learning ShanghaiTech University NeurIPS 2023 [PUB] [SUPP] [PDF] [CODE]
Solving a Class of Non-Convex Minimax Optimization in Federated Learning University of Pittsburgh NeurIPS 2023 [PUB] [SUPP] [PDF] [CODE]
Federated Learning via Meta-Variational Dropout SNU NeurIPS 2023 [PUB] [CODE]
Improved Communication Efficiency in Federated Natural Policy Gradient via ADMM-based Gradient Updates Purdue University NeurIPS 2023 [PUB] [SUPP] [PDF]
SPACE: Single-round Participant Amalgamation for Contribution Evaluation in Federated Learning NTU NeurIPS 2023 [PUB] [CODE]
Fed-FA: Theoretically Modeling Client Data Divergence for Federated Language Backdoor Defense PKU; Tencent NeurIPS 2023 [PUB] [SUPP]
FedFed: Feature Distillation against Data Heterogeneity in Federated Learning BUAA; HKBU NeurIPS 2023 [PUB] [PDF] [CODE]
PRIOR: Personalized Prior for Reactivating the Information Overlooked in Federated Learning SCU NeurIPS 2023 [PUB] [SUPP] [PDF] [CODE] [解读]
Spectral Co-Distillation for Personalized Federated Learning SUTD NeurIPS 2023 [PUB]
Breaking the Communication-Privacy-Accuracy Tradeoff with $f$-Differential Privacy ZJU NeurIPS 2023 [PUB] [SUPP] [PDF]
Exact Optimality of Communication-Privacy-Utility Tradeoffs in Distributed Mean Estimation Stanford University NeurIPS 2023 [PUB] [SUPP] [PDF] [CODE]
(Amplified) Banded Matrix Factorization: A unified approach to private training Google DeepMind NeurIPS 2023 [PUB] [SUPP] [PDF]
Aggregating Capacity in FL through Successive Layer Training for Computationally-Constrained Devices KIT NeurIPS 2023 [PUB] [SUPP] [PDF] [CODE]
Privacy Amplification via Compression: Achieving the Optimal Privacy-Accuracy-Communication Trade-off in Distributed Mean Estimation Stanford University NeurIPS 2023 [PUB] [SUPP] [PDF]
Incentivizing Honesty among Competitors in Collaborative Learning and Optimization ETH Zurich NeurIPS 2023 [PUB] [SUPP] [PDF]
Resilient Constrained Learning UPenn NeurIPS 2023 [PUB] [SUPP] [PDF]
A Computation and Communication Efficient Method for Distributed Nonconvex Problems in the Partial Participation Setting KAUST NeurIPS 2023 [PUB] [SUPP] [PDF] [CODE]
Collaboratively Learning Linear Models with Structured Missing Data Stanford University NeurIPS 2023 [PUB] [SUPP] [PDF] [CODE]
Gradient Descent with Linearly Correlated Noise: Theory and Applications to Differential Privacy EPFL NeurIPS 2023 [PUB] [SUPP] [PDF]
Fast Optimal Locally Private Mean Estimation via Random Projections Apple Inc. NeurIPS 2023 [PUB] [SUPP] [PDF] [CODE]
Contextual Stochastic Bilevel Optimization EPFL; ETH Zürich NeurIPS 2023 [PUB] [SUPP] [PDF]
Understanding Deep Gradient Leakage via Inversion Influence Functions MSU; Michigan State University; University of Texas at Austin NeurIPS 2023 [PUB] [SUPP] [PDF] [CODE]
Inner Product-based Neural Network Similarity Purdue University NeurIPS 2023 [PUB] [SUPP]
Correlation Aware Sparsified Mean Estimation Using Random Projection CMU NeurIPS 2023 [PUB] [SUPP] [PDF] [CODE]
TIES-Merging: Resolving Interference When Merging Models UNC NeurIPS 2023 [PUB] [SUPP] [PDF] [CODE]
Global Update Tracking: A Decentralized Learning Algorithm for Heterogeneous Data Purdue University NeurIPS 2023 [PUB] [SUPP] [PDF] [CODE]
Large-Scale Distributed Learning via Private On-Device LSH UMD NeurIPS 2023 [PUB] [SUPP] [PDF]
Faster Relative Entropy Coding with Greedy Rejection Coding University of Cambridge NeurIPS 2023 [PUB] [SUPP] [PDF] [CODE]
Global Convergence Analysis of Local SGD for Two-layer Neural Network without Overparameterization SJTU NeurIPS 2023 [PUB] [SUPP]
Momentum Provably Improves Error Feedback! ETH AI Center; ETH Zurich NeurIPS 2023 [PUB] [SUPP] [PDF]
Strategic Data Sharing between Competitors Sofia University NeurIPS 2023 [PUB] [SUPP] [PDF]
H-nobs: Achieving Certified Fairness and Robustness in Distributed Learning on Heterogeneous Datasets GMU NeurIPS 2023 [PUB]
Wyze Rule: Federated Rule Dataset for Rule Recommendation Benchmarking Wyze Labs NeurIPS Datasets and Benchmarks 2023 [PUB] [SUPP] [DATASET]
Towards Federated Foundation Models: Scalable Dataset Pipelines for Group-Structured Learning Google Research NeurIPS Datasets and Benchmarks 2023 [PUB] [PDF] [DATASET]
Text-driven Prompt Generation for Vision-Language Models in Federated Learning NeurIPS workshop 2023 [PUB]
HePCo: Data-Free Heterogeneous Prompt Consolidation for Continual Federated Learning NeurIPS workshop 2023 [PUB]
Beyond Gradient and Priors in Privacy Attacks: Leveraging Pooler Layer Inputs of Language Models in Federated Learning NeurIPS workshop 2023 [PUB]
FOCUS: Fairness via Agent-Awareness for Federated Learning on Heterogeneous Data NeurIPS workshop 2023 [PUB]
FedSoL: Bridging Global Alignment and Local Generality in Federated Learning NeurIPS workshop 2023 [PUB]
One-shot Empirical Privacy Estimation for Federated Learning NeurIPS workshop 2023 [PUB]
Profit: Benchmarking Personalization and Robustness Trade-off in Federated Prompt Tuning NeurIPS workshop 2023 [PUB]
SLoRA: Federated Parameter Efficient Fine-Tuning of Language Models NeurIPS workshop 2023 [PUB]
The Fair Value of Data Under Heterogeneous Privacy Constraints in Federated Learning NeurIPS workshop 2023 [PUB]
Towards Building the FederatedGPT: Federated Instruction Tuning NeurIPS workshop 2023 [PUB]
Federated Learning for Speech Recognition: Revisiting Current Trends Towards Large-Scale ASR NeurIPS workshop 2023 [PUB]
LASER: Linear Compression in Wireless Distributed Optimization NeurIPS workshop 2023 [PUB]
MARINA Meets Matrix Stepsizes: Variance Reduced Distributed Non-Convex Optimization NeurIPS workshop 2023 [PUB]
TAMUNA: Doubly Accelerated Federated Learning with Local Training, Compression, and Partial Participation NeurIPS workshop 2023 [PUB]
An Empirical Evaluation of Federated Contextual Bandit Algorithms NeurIPS workshop 2023 [PUB]
RealFM: A Realistic Mechanism to Incentivize Data Contribution and Device Participation NeurIPS workshop 2023 [PUB]
FDAPT: Federated Domain-adaptive Pre-training for Language Models NeurIPS workshop 2023 [PUB]
Making Batch Normalization Great in Federated Deep Learning NeurIPS workshop 2023 [PUB]
Correlated Noise Provably Beats Independent Noise for Differentially Private Learning NeurIPS workshop 2023 [PUB]
Parameter Averaging Laws for Multitask Language Models NeurIPS workshop 2023 [PUB]
Breaking Physical and Linguistic Borders: Multilingual Federated Prompt Tuning for Low-Resource Languages NeurIPS workshop 2023 [PUB]
Beyond Parameter Averaging in Model Aggregation NeurIPS workshop 2023 [PUB]
Augmenting Federated Learning with Pretrained Transformers NeurIPS workshop 2023 [PUB]
Consensus Optimization at Representation: Improving Personalized Federated Learning via Data-Centric Regularization NeurIPS workshop 2023 [PUB]
DPZero: Dimension-Independent and Differentially Private Zeroth-Order Optimization NeurIPS workshop 2023 [PUB]
Leveraging Foundation Models to Improve Lightweight Clients in Federated Learning NeurIPS workshop 2023 [PUB]
FedML-HE: An Efficient Homomorphic-Encryption-Based Privacy-Preserving Federated Learning System NeurIPS workshop 2023 [PUB]
Learning Optimizers for Local SGD NeurIPS workshop 2023 [PUB]
Exploring User-level Gradient Inversion with a Diffusion Prior NeurIPS workshop 2023 [PUB]
User Inference Attacks on Large Language Models NeurIPS workshop 2023 [PUB]
FedLDA: Personalized Federated Learning Through Collaborative Linear Discriminant Analysis NeurIPS workshop 2023 [PUB]
Heterogeneous LoRA for Federated Fine-tuning of On-device Foundation Models NeurIPS workshop 2023 [PUB]
Backdoor Threats from Compromised Foundation Models to Federated Learning NeurIPS workshop 2023 [PUB]
MOFL/D: A Federated Multi-objective Learning Framework with Decomposition NeurIPS workshop 2023 [PUB]
Absolute Variation Distance: an Inversion Attack Evaluation Metric for Federated Learning NeurIPS workshop 2023 [PUB]
Fed3R: Recursive Ridge Regression for Federated Learning with strong pre-trained models NeurIPS workshop 2023 [PUB]
FedFN: Feature Normalization for Alleviating Data Heterogeneity Problem in Federated Learning NeurIPS workshop 2023 [PUB]
Private and Personalized Histogram Estimation in a Federated Setting NeurIPS workshop 2023 [PUB]
The Aggregation–Heterogeneity Trade-off in Federated Learning PKU COLT 2023 [PUB]
FLASH: Automating federated learning using CASH Rensselaer Polytechnic Institute UAI 2023 [PUB] [SUPP] [MATERIAL]
Personalized federated domain adaptation for item-to-item recommendation AWS AI Labs UAI 2023 [PUB] [PDF] [SUPP] [MATERIAL] [CODE]
Fed-LAMB: Layer-wise and Dimension-wise Locally Adaptive Federated Learning Baidu Research UAI 2023 [PUB] [PDF] [SUPP] [MATERIAL]
Federated learning of models pre-trained on different features with consensus graphs IBM Research UAI 2023 [PUB] [SUPP] [MATERIAL] [CODE]
Fast Heterogeneous Federated Learning with Hybrid Client Selection NWPU UAI 2023 [PUB] [SUPP] [MATERIAL] [PDF]
Learning To Invert: Simple Adaptive Attacks for Gradient Inversion in Federated Learning Cornell University UAI 2023 [PUB] [PDF] [SUPP] [MATERIAL] [CODE]
Dynamic Regularized Sharpness Aware Minimization in Federated Learning: Approaching Global Consistency and Smooth Landscape The University of Sydney ICML 2023 [PUB] [PDF] [SLIDES]
Analysis of Error Feedback in Federated Non-Convex Optimization with Biased Compression: Fast Convergence and Partial Participation LinkedIn Ads ICML 2023 [PUB] [PDF]
FedHPO-Bench: A Benchmark Suite for Federated Hyperparameter Optimization Alibaba Group ICML 2023 [PUB] [PDF] [CODE]
Federated Conformal Predictors for Distributed Uncertainty Quantification MIT ICML 2023 [PUB] [PDF] [CODE]
Federated Adversarial Learning: A Framework with Convergence Analysis UBC ICML 2023 [PUB] [PDF]
Federated Heavy Hitter Recovery under Linear Sketching Google Research ICML 2023 [PUB] [PDF] [CODE]
Doubly Adversarial Federated Bandits London School of Economics and Political Science ICML 2023 [PUB] [PDF] [CODE]
Achieving Linear Speedup in Non-IID Federated Bilevel Learning UC ICML 2023 [PUB] [PDF]
One-Shot Federated Conformal Prediction Université Paris-Saclay ICML 2023 [PUB] [PDF] [CODE]
Federated Online and Bandit Convex Optimization TTIC ICML 2023 [PUB]
Federated Linear Contextual Bandits with User-level Differential Privacy The Pennsylvania State University ICML 2023 [PUB] [PDF]
Vertical Federated Graph Neural Network for Recommender System NUS ICML 2023 [PUB] [PDF] [CODE]
Communication-Efficient Federated Hypergradient Computation via Aggregated Iterative Differentiation University at Buffalo ICML 2023 [PUB] [PDF]
Towards Understanding Ensemble Distillation in Federated Learning KAIST ICML 2023 [PUB]
Personalized Subgraph Federated Learning KAIST ICML 2023 [PUB] [PDF] [CODE]
Conformal Prediction for Federated Uncertainty Quantification Under Label Shift Lagrange Mathematics and Computing Research Center; CMAP ICML 2023 [PUB] [PDF]
Secure Federated Correlation Test and Entropy Estimation CMU ICML 2023 [PUB] [PDF]
Out-of-Distribution Generalization of Federated Learning via Implicit Invariant Relationships JLU ICML 2023 [PUB] [CODE]
Personalized Federated Learning under Mixture of Distributions UCLA ICML 2023 [PUB] [PDF] [CODE]
FedDisco: Federated Learning with Discrepancy-Aware Collaboration SJTU ICML 2023 [PUB] [PDF] [CODE]
Anchor Sampling for Federated Learning with Partial Client Participation Purdue University ICML 2023 [PUB] [PDF] [CODE]
Private Federated Learning with Autotuned Compression JHU; Google ICML 2023 [PUB] [PDF]
Fast Federated Machine Unlearning with Nonlinear Functional Theory Auburn University ICML 2023 [PUB]
On the Convergence of Federated Averaging with Cyclic Client Participation CMU ICML 2023 [PUB] [PDF]
Revisiting Weighted Aggregation in Federated Learning with Neural Networks ZJU ICML 2023 [PUB] [PDF] [CODE]
The Blessing of Heterogeneity in Federated Q-Learning: Linear Speedup and Beyond CMU ICML 2023 [PUB] [PDF] [SLIDES]
GuardHFL: Privacy Guardian for Heterogeneous Federated Learning UESTC; NTU ICML 2023 [PUB]
Flash: Concept Drift Adaptation in Federated Learning University of Massachusetts ICML 2023 [PUB]
DoCoFL: Downlink Compression for Cross-Device Federated Learning VMware Research; Technion ICML 2023 [PUB] [PDF]
FeDXL: Provable Federated Learning for Deep X-Risk Optimization Texas A&M University ICML 2023 [PUB] [PDF] [CODE]
No One Idles: Efficient Heterogeneous Federated Learning with Parallel Edge and Server Computation HIT ICML 2023 [PUB] [CODE]
Personalized Federated Learning with Inferred Collaboration Graphs SJTU ICML 2023 [PUB] [CODE]
Optimizing the Collaboration Structure in Cross-Silo Federated Learning UIUC ICML 2023 [PUB] [PDF] [CODE] [SLIDES]
TabLeak: Tabular Data Leakage in Federated Learning ETH Zurich ICML 2023 [PUB] [PDF] [CODE]
FedCR: Personalized Federated Learning Based on Across-Client Common Representation with Conditional Mutual Information Regularization SJTU ICML 2023 [PUB] [CODE]
Fed-CBS: A Heterogeneity-Aware Client Sampling Mechanism for Federated Learning via Class-Imbalance Reduction Duke University ICML 2023 [PUB] [PDF]
Privacy-Aware Compression for Federated Learning Through Numerical Mechanism Design Meta AI ICML 2023 [PUB] [PDF] [CODE]
SRATTA: Sample Re-ATTribution Attack of Secure Aggregation in Federated Learning Owkin Inc. ICML 2023 [PUB] [PDF] [CODE]
Improving the Model Consistency of Decentralized Federated Learning THU ICML 2023 [PUB] [PDF]
Efficient Personalized Federated Learning via Sparse Model-Adaptation Alibaba Group ICML 2023 [PUB] [PDF] [CODE]
From Noisy Fixed-Point Iterations to Private ADMM for Centralized and Federated Learning Univ. Lille ICML 2023 [PUB] [PDF] [CODE]
LeadFL: Client Self-Defense against Model Poisoning in Federated Learning TUD ICML 2023 [PUB] [CODE]
Chameleon: Adapting to Peer Images for Planting Durable Backdoors in Federated Learning HKUST ICML 2023 [PUB] [PDF] [CODE]
FedVS: Straggler-Resilient and Privacy-Preserving Vertical Federated Learning for Split Models HKUST ICML 2023 [PUB] [PDF]
FedBR: Improving Federated Learning on Heterogeneous Data via Local Learning Bias Reduction CUHK; The Shenzhen Institute of Artificial Intelligence and Robotics for Society ICML 2023 [PUB] [PDF] [CODE]
Towards Unbiased Training in Federated Open-world Semi-supervised Learning PolyU ICML 2023 [PUB] [PDF] [SLIDES]
Cocktail Party Attack: Breaking Aggregation-Based Privacy in Federated Learning Using Independent Component Analysis Georgia Tech; Meta AI ICML 2023 [PUB] [PDF]
Surrogate Model Extension (SME): A Fast and Accurate Weight Update Attack on Federated Learning KU Leuven ICML 2023 [PUB] [PDF] [CODE]
Fair yet Asymptotically Equal Collaborative Learning NUS ICML 2023 [PUB] [PDF] [CODE]
Sketching for First Order Method: Efficient Algorithm for Low-Bandwidth Channel and Vulnerability Adobe Research ICML 2023 [PUB] [PDF]
Adversarial Collaborative Learning on Non-IID Features UC Berkeley; NUS ICML 2023 [PUB]
XTab: Cross-table Pretraining for Tabular Transformers EPFL; Cornell University; AWS ICML 2023 [PUB] [PDF] [CODE]
Momentum Ensures Convergence of SIGNSGD under Weaker Assumptions NUDT ICML 2023 [PUB]
Byzantine-Robust Learning on Heterogeneous Data via Gradient Splitting Key Lab of Intelligent Computing Based Big Data of Zhejiang Province; ZJU; Sony Al ICML 2023 [PUB] [PDF] [CODE]
LESS-VFL: Communication-Efficient Feature Selection for Vertical Federated Learning Rensselaer Polytechnic Institute ICML 2023 [PUB] [PDF]
FedAvg Converges to Zero Training Loss Linearly for Overparameterized Multi-Layer Neural Networks University of Minnesota ICML 2023 [PUB]
Addressing Budget Allocation and Revenue Allocation in Data Market Environments Using an Adaptive Sampling Algorithm University of Chicago ICML 2023 [PUB] [PDF] [CODE]
Ensemble and continual federated learning for classification tasks. Universidade de Santiago de Compostela Mach Learn 2023 [PUB] [PDF]
FAC-fed: Federated adaptation for fairness and concept drift aware stream classification Leibniz University of Hannover Mach Learn 2023 [PUB]
Robust federated learning under statistical heterogeneity via hessian-weighted aggregation Deakin University Mach Learn 2023 [PUB]
FedLab: A Flexible Federated Learning Framework :fire: UESTC; Peng Cheng Lab JMLR 2023 [PUB] [PDF] [CODE]
Minimax Estimation for Personalized Federated Learning: An Alternative between FedAvg and Local Training? JMLR 2023 [PUB]
Memory-Based Optimization Methods for Model-Agnostic Meta-Learning and Personalized Federated Learning TAMU JMLR 2023 [PUB] [PDF] [CODE]
A First Look into the Carbon Footprint of Federated Learning University of Cambridge JMLR 2023 [PUB] [PDF]
Attacks against Federated Learning Defense Systems and their Mitigation The University of Newcastle JMLR 2023 [PUB] [CODE]
A General Theory for Federated Optimization with Asynchronous and Heterogeneous Clients Updates Universit ́e Cˆ ote d’Azur JMLR 2023 [PUB] [PDF] [CODE]
Tighter Regret Analysis and Optimization of Online Federated Learning Hanyang University TPAMI 2023 [PUB] [PDF]
Efficient Federated Learning Via Local Adaptive Amended Optimizer With Linear Speedup University of Sydney TPAMI 2023 [PDF]
Federated Learning Via Inexact ADMM. BJTU TPAMI 2023 [PUB] [PDF] [CODE]
FedIPR: Ownership Verification for Federated Deep Neural Network Models SJTU TPAMI 2023 [PUB] [PDF] [CODE] [解读]
Decentralized Federated Averaging NUDT TPAMI 2023 [PUB] [PDF]
Personalized Federated Learning with Feature Alignment and Classifier Collaboration THU ICLR 2023 [PUB] [CODE]
MocoSFL: enabling cross-client collaborative self-supervised learning ASU ICLR 2023 [PUB] [CODE]
Single-shot General Hyper-parameter Optimization for Federated Learning IBM ICLR 2023 [PUB] [PDF] [CODE]
Where to Begin? Exploring the Impact of Pre-Training and Initialization in Federated Facebook ICLR 2023 [PUB] [PDF] [CODE]
FedExP: Speeding up Federated Averaging via Extrapolation CMU ICLR 2023 [PUB] [PDF] [CODE]
Turning the Curse of Heterogeneity in Federated Learning into a Blessing for Out-of-Distribution Detection MSU ICLR 2023 [PUB] [CODE]
DASHA: Distributed Nonconvex Optimization with Communication Compression and Optimal Oracle Complexity KAUST ICLR 2023 [PUB] [PDF] [CODE]
Machine Unlearning of Federated Clusters University of Illinois ICLR 2023 [PUB] [PDF] [CODE]
Federated Neural Bandits NUS ICLR 2023 [PUB] [PDF] [CODE]
FedFA: Federated Feature Augmentation ETH Zurich ICLR 2023 [PUB] [PDF] [CODE]
Federated Learning as Variational Inference: A Scalable Expectation Propagation Approach CMU ICLR 2023 [PUB] [PDF] [CODE]
Better Generative Replay for Continual Federated Learning University of Virginia ICLR 2023 [PUB] [CODE]
Federated Learning from Small Datasets IKIM ICLR 2023 [PUB] [PDF]
Federated Nearest Neighbor Machine Translation USTC ICLR 2023 [PUB] [PDF]
Meta Knowledge Condensation for Federated Learning A*STAR ICLR 2023 [PUB] [PDF]
Test-Time Robust Personalization for Federated Learning EPFL ICLR 2023 [PUB] [PDF] [CODE]
DepthFL : Depthwise Federated Learning for Heterogeneous Clients SNU ICLR 2023 [PUB]
Towards Addressing Label Skews in One-Shot Federated Learning NUS ICLR 2023 [PUB] [CODE]
Towards Understanding and Mitigating Dimensional Collapse in Heterogeneous Federated Learning NUS ICLR 2023 [PUB] [PDF] [CODE]
Panning for Gold in Federated Learning: Targeted Text Extraction under Arbitrarily Large-Scale Aggregation UMD ICLR 2023 [PUB] [CODE]
SWIFT: Rapid Decentralized Federated Learning via Wait-Free Model Communication UMD ICLR 2023 [PUB] [PDF] [CODE]
Private Federated Learning Without a Trusted Server: Optimal Algorithms for Convex Losses USC ICLR 2023 [PUB] [PDF] [CODE]
Effective passive membership inference attacks in federated learning against overparameterized models Purdue University ICLR 2023 [PUB]
FiT: Parameter Efficient Few-shot Transfer Learning for Personalized and Federated Image Classification University of Cambridge ICLR 2023 [PUB] [PDF] [CODE]
Multimodal Federated Learning via Contrastive Representation Ensemble THU ICLR 2023 [PUB] [PDF] [CODE]
Faster federated optimization under second-order similarity Princeton University ICLR 2023 [PUB] [PDF] [CODE]
FedSpeed: Larger Local Interval, Less Communication Round, and Higher Generalization Accuracy University of Sydney ICLR 2023 [PUB] [CODE]
The Best of Both Worlds: Accurate Global and Personalized Models through Federated Learning with Data-Free Hyper-Knowledge Distillation utexas ICLR 2023 [PUB] [PDF] [CODE]
PerFedMask: Personalized Federated Learning with Optimized Masking Vectors UBC ICLR 2023 [PUB] [CODE]
EPISODE: Episodic Gradient Clipping with Periodic Resampled Corrections for Federated Learning with Heterogeneous Data GMU ICLR 2023 [PUB] [CODE]
FedDAR: Federated Domain-Aware Representation Learning Harvard ICLR 2023 [PUB] [PDF] [CODE]
Share Your Representation Only: Guaranteed Improvement of the Privacy-Utility Tradeoff in Federated Learning upenn ICLR 2023 [PUB] [CODE]
FLIP: A Provable Defense Framework for Backdoor Mitigation in Federated Learning Purdue University ICLR 2023 [PUB] [PDF] [CODE]
Generalization Bounds for Federated Learning: Fast Rates, Unparticipating Clients and Unbounded Losses RUC ICLR 2023 [PUB]
Efficient Federated Domain Translation Purdue University ICLR 2023 [PUB] [CODE]
On the Importance and Applicability of Pre-Training for Federated Learning OSU ICLR 2023 [PUB] [PDF] [CODE]
Decepticons: Corrupted Transformers Breach Privacy in Federated Learning for Language Models UMD ICLR 2023 [PUB] [PDF] [CODE]
A Statistical Framework for Personalized Federated Learning and Estimation: Theory, Algorithms, and Privacy UCLA ICLR 2023 [PUB] [PDF]
Instance-wise Batch Label Restoration via Gradients in Federated Learning BUAA ICLR 2023 [PUB] [CODE]
Data-Free One-Shot Federated Learning Under Very High Statistical Heterogeneity College of William and Mary ICLR 2023 [PUB]
CANIFE: Crafting Canaries for Empirical Privacy Measurement in Federated Learning University of Warwick ICLR 2023 [PUB] [PDF] [CODE]
Sparse Random Networks for Communication-Efficient Federated Learning Stanford ICLR 2023 [PUB] [PDF] [CODE]
Combating Exacerbated Heterogeneity for Robust Decentralized Models HKBU ICLR 2023 [PUB] [CODE]
Hyperparameter Optimization through Neural Network Partitioning University of Cambridge ICLR 2023 [PUB] [PDF]
Does Decentralized Learning with Non-IID Unlabeled Data Benefit from Self Supervision? MIT ICLR 2023 [PUB] [PDF] [CODE]
Variance Reduction is an Antidote to Byzantines: Better Rates, Weaker Assumptions and Communication Compression as a Cherry on the Top mbzuai ICLR 2023 [PUB] [PDF] [CODE]
Dual Diffusion Implicit Bridges for Image-to-Image Translation Stanford ICLR 2023 [PUB] [PDF] [CODE]
An accurate, scalable and verifiable protocol for federated differentially private averaging INRIA Lille Mach Learn 2022 [PUB] [PDF]
Federated online clustering of bandits. CUHK UAI 2022 [PUB] [PDF] [CODE]
Privacy-aware compression for federated data analysis. Meta AI UAI 2022 [PUB] [PDF] [CODE]
Faster non-convex federated learning via global and local momentum. UTEXAS UAI 2022 [PUB] [PDF]
Fedvarp: Tackling the variance due to partial client participation in federated learning. CMU UAI 2022 [PUB] [PDF]
SASH: Efficient secure aggregation based on SHPRG for federated learning CAS; CASTEST UAI 2022 [PUB] [PDF]
Bayesian federated estimation of causal effects from observational data NUS UAI 2022 [PUB] [PDF]
Communication-Efficient Randomized Algorithm for Multi-Kernel Online Federated Learning Hanyang University TPAMI 2022 [PUB]
Lazily Aggregated Quantized Gradient Innovation for Communication-Efficient Federated Learning ZJU TPAMI 2022 [PUB] [CODE]
Communication Acceleration of Local Gradient Methods via an Accelerated Primal-Dual Algorithm with an Inexact Prox Moscow Institute of Physics and Technology NeurIPS 2022 [PUB] [PDF]
LAMP: Extracting Text from Gradients with Language Model Priors ETHZ NeurIPS 2022 [PUB] [CODE]
FedAvg with Fine Tuning: Local Updates Lead to Representation Learning utexas NeurIPS 2022 [PUB] [PDF]
On Convergence of FedProx: Local Dissimilarity Invariant Bounds, Non-smoothness and Beyond NUIST NeurIPS 2022 [PUB] [PDF]
Improved Differential Privacy for SGD via Optimal Private Linear Operators on Adaptive Streams WISC NeurIPS 2022 [PUB] [CODE]
Decentralized Gossip-Based Stochastic Bilevel Optimization over Communication Networks Columbia University NeurIPS 2022 [PUB] [PDF]
Asymptotic Behaviors of Projected Stochastic Approximation: A Jump Diffusion Perspective PKU NeurIPS 2022 [PUB]
Subspace Recovery from Heterogeneous Data with Non-isotropic Noise Stanford NeurIPS 2022 [PUB] [PDF]
EF-BV: A Unified Theory of Error Feedback and Variance Reduction Mechanisms for Biased and Unbiased Compression in Distributed Optimization KAUST NeurIPS 2022 [PUB] [PDF]
On-Demand Sampling: Learning Optimally from Multiple Distributions UC Berkeley NeurIPS 2022 [PUB] [CODE]
Improved Utility Analysis of Private CountSketch ITU NeurIPS 2022 [PUB] [PDF] [CODE]
Rate-Distortion Theoretic Bounds on Generalization Error for Distributed Learning HUAWEI NeurIPS 2022 [PUB] [CODE]
Decentralized Local Stochastic Extra-Gradient for Variational Inequalities phystech NeurIPS 2022 [PUB] [PDF]
BEER: Fast O(1/T) Rate for Decentralized Nonconvex Optimization with Communication Compression Princeton NeurIPS 2022 [PUB] [PDF] [CODE]
Escaping Saddle Points with Bias-Variance Reduced Local Perturbed SGD for Communication Efficient Nonconvex Distributed Learning The University of Tokyo NeurIPS 2022 [PUB] [PDF]
Near-Optimal Collaborative Learning in Bandits INRIA; Inserm NeurIPS 2022 [PUB] [PDF] [CODE]
Distributed Methods with Compressed Communication for Solving Variational Inequalities, with Theoretical Guarantees phystech NeurIPS 2022 [PUB] [PDF]
Towards Optimal Communication Complexity in Distributed Non-Convex Optimization TTIC NeurIPS 2022 [PUB] [CODE]
FedPop: A Bayesian Approach for Personalised Federated Learning Skoltech NeurIPS 2022 [PUB] [PDF]
Fairness in Federated Learning via Core-Stability UIUC NeurIPS 2022 [PUB] [CODE]
SecureFedYJ: a safe feature Gaussianization protocol for Federated Learning Sorbonne Université NeurIPS 2022 [PUB] [PDF]
FedRolex: Model-Heterogeneous Federated Learning with Rolling Submodel Extraction MSU NeurIPS 2022 [PUB] [CODE]
On Sample Optimality in Personalized Collaborative and Federated Learning INRIA NeurIPS 2022 [PUB]
DReS-FL: Dropout-Resilient Secure Federated Learning for Non-IID Clients via Secret Data Sharing HKUST NeurIPS 2022 [PUB] [PDF]
FairVFL: A Fair Vertical Federated Learning Framework with Contrastive Adversarial Learning THU NeurIPS 2022 [PUB]
Variance Reduced ProxSkip: Algorithm, Theory and Application to Federated Learning KAUST NeurIPS 2022 [PUB] [PDF]
VF-PS: How to Select Important Participants in Vertical Federated Learning, Efficiently and Securely? WHU NeurIPS 2022 [PUB] [CODE]
DENSE: Data-Free One-Shot Federated Learning ZJU NeurIPS 2022 [PUB] [PDF]
CalFAT: Calibrated Federated Adversarial Training with Label Skewness ZJU NeurIPS 2022 [PUB] [PDF]
SAGDA: Achieving O(ϵ−2) Communication Complexity in Federated Min-Max Learning OSU NeurIPS 2022 [PUB] [PDF]
Taming Fat-Tailed (“Heavier-Tailed” with Potentially Infinite Variance) Noise in Federated Learning OSU NeurIPS 2022 [PUB] [PDF]
Personalized Federated Learning towards Communication Efficiency, Robustness and Fairness PKU NeurIPS 2022 [PUB]
Federated Submodel Optimization for Hot and Cold Data Features SJTU NeurIPS 2022 [PUB]
BooNTK: Convexifying Federated Learning using Bootstrapped Neural Tangent Kernels UC Berkeley NeurIPS 2022 [PUB] [PDF]
Byzantine-tolerant federated Gaussian process regression for streaming data PSU NeurIPS 2022 [PUB] [CODE]
SoteriaFL: A Unified Framework for Private Federated Learning with Communication Compression CMU NeurIPS 2022 [PUB] [PDF]
Coresets for Vertical Federated Learning: Regularized Linear Regression and K-Means Clustering Yale NeurIPS 2022 [PUB] [PDF] [CODE]
Communication Efficient Federated Learning for Generalized Linear Bandits University of Virginia NeurIPS 2022 [PUB] [CODE]
Recovering Private Text in Federated Learning of Language Models Princeton NeurIPS 2022 [PUB] [PDF] [CODE]
Federated Learning from Pre-Trained Models: A Contrastive Learning Approach UTS NeurIPS 2022 [PUB] [PDF]
Global Convergence of Federated Learning for Mixed Regression Northeastern University NeurIPS 2022 [PUB] [PDF]
Resource-Adaptive Federated Learning with All-In-One Neural Composition JHU NeurIPS 2022 [PUB]
Self-Aware Personalized Federated Learning Amazon NeurIPS 2022 [PUB] [PDF]
A Communication-efficient Algorithm with Linear Convergence for Federated Minimax Learning Northeastern University NeurIPS 2022 [PUB] [PDF]
An Adaptive Kernel Approach to Federated Learning of Heterogeneous Causal Effects NUS NeurIPS 2022 [PUB]
Sharper Convergence Guarantees for Asynchronous SGD for Distributed and Federated Learning EPFL NeurIPS 2022 [PUB] [PDF]
Personalized Online Federated Multi-Kernel Learning UCI NeurIPS 2022 [PUB]
SemiFL: Semi-Supervised Federated Learning for Unlabeled Clients with Alternate Training Duke University NeurIPS 2022 [PUB] [PDF] [CODE]
A Unified Analysis of Federated Learning with Arbitrary Client Participation IBM NeurIPS 2022 [PUB] [PDF]
Preservation of the Global Knowledge by Not-True Distillation in Federated Learning KAIST NeurIPS 2022 [PUB] [PDF] [CODE]
FedSR: A Simple and Effective Domain Generalization Method for Federated Learning University of Oxford NeurIPS 2022 [PUB] [CODE]
Factorized-FL: Personalized Federated Learning with Parameter Factorization & Similarity Matching KAIST NeurIPS 2022 [PUB] [PDF] [CODE]
A Simple and Provably Efficient Algorithm for Asynchronous Federated Contextual Linear Bandits UC NeurIPS 2022 [PUB] [PDF]
Learning to Attack Federated Learning: A Model-based Reinforcement Learning Attack Framework Tulane University NeurIPS 2022 [PUB]
On Privacy and Personalization in Cross-Silo Federated Learning CMU NeurIPS 2022 [PUB] [PDF]
A Coupled Design of Exploiting Record Similarity for Practical Vertical Federated Learning NUS NeurIPS 2022 [PUB] [PDF] [CODE]
FLamby: Datasets and Benchmarks for Cross-Silo Federated Learning in Realistic Healthcare Settings Owkin NeurIPS Datasets and Benchmarks 2022 [PUB] [CODE]
A Tree-based Model Averaging Approach for Personalized Treatment Effect Estimation from Heterogeneous Data Sources University of Pittsburgh ICML 2022 [PUB] [PDF] [CODE]
Fast Composite Optimization and Statistical Recovery in Federated Learning SJTU ICML 2022 [PUB] [PDF] [CODE]
Personalization Improves Privacy-Accuracy Tradeoffs in Federated Learning NYU ICML 2022 [PUB] [PDF] [CODE]
The Fundamental Price of Secure Aggregation in Differentially Private Federated Learning :fire: Stanford; Google Research ICML 2022 [PUB] [PDF] [CODE] [SLIDE]
The Poisson Binomial Mechanism for Unbiased Federated Learning with Secure Aggregation Stanford; Google Research ICML 2022 [PUB] [PDF] [CODE]
DisPFL: Towards Communication-Efficient Personalized Federated Learning via Decentralized Sparse Training USTC ICML 2022 [PUB] [PDF] [CODE]
FedNew: A Communication-Efficient and Privacy-Preserving Newton-Type Method for Federated Learning University of Oulu ICML 2022 [PUB] [PDF] [CODE]
DAdaQuant: Doubly-adaptive quantization for communication-efficient Federated Learning University of Cambridge ICML 2022 [PUB] [PDF] [SLIDE] [CODE]
Accelerated Federated Learning with Decoupled Adaptive Optimization Auburn University ICML 2022 [PUB] [PDF]
Federated Reinforcement Learning: Linear Speedup Under Markovian Sampling Georgia Tech ICML 2022 [PUB] [PDF]
Multi-Level Branched Regularization for Federated Learning Seoul National University ICML 2022 [PUB] [PDF] [CODE] [PAGE]
FedScale: Benchmarking Model and System Performance of Federated Learning at Scale :fire: University of Michigan ICML 2022 [PUB] [PDF] [CODE]
Federated Learning with Positive and Unlabeled Data XJTU ICML 2022 [PUB] [PDF] [CODE]
Deep Neural Network Fusion via Graph Matching with Applications to Model Ensemble and Federated Learning SJTU ICML 2022 [PUB] [CODE]
Orchestra: Unsupervised Federated Learning via Globally Consistent Clustering University of Michigan ICML 2022 [PUB] [PDF] [CODE]
Disentangled Federated Learning for Tackling Attributes Skew via Invariant Aggregation and Diversity Transferring USTC ICML 2022 [PUB] [PDF] [CODE] [SLIDE] [解读]
Architecture Agnostic Federated Learning for Neural Networks The University of Texas at Austin ICML 2022 [PUB] [PDF] [SLIDE]
Personalized Federated Learning through Local Memorization Inria ICML 2022 [PUB] [PDF] [CODE]
Proximal and Federated Random Reshuffling KAUST ICML 2022 [PUB] [PDF] [CODE]
Federated Learning with Partial Model Personalization University of Washington ICML 2022 [PUB] [PDF] [CODE]
Generalized Federated Learning via Sharpness Aware Minimization University of South Florida ICML 2022 [PUB] [PDF]
FedNL: Making Newton-Type Methods Applicable to Federated Learning KAUST ICML 2022 [PUB] [PDF] [VIDEO] [SLIDE]
Federated Minimax Optimization: Improved Convergence Analyses and Algorithms CMU ICML 2022 [PUB] [PDF] [SLIDE]
Virtual Homogeneity Learning: Defending against Data Heterogeneity in Federated Learning Hong Kong Baptist University ICML 2022 [PUB] [PDF] [CODE] [解读]
FedNest: Federated Bilevel, Minimax, and Compositional Optimization University of Michigan ICML 2022 [PUB] [PDF] [CODE]
EDEN: Communication-Efficient and Robust Distributed Mean Estimation for Federated Learning VMware Research ICML 2022 [PUB] [PDF] [CODE]
Communication-Efficient Adaptive Federated Learning Pennsylvania State University ICML 2022 [PUB] [PDF]
ProgFed: Effective, Communication, and Computation Efficient Federated Learning by Progressive Training CISPA Helmholz Center for Information Security ICML 2022 [PUB] [PDF] [SLIDE] [CODE]
Fishing for User Data in Large-Batch Federated Learning via Gradient Magnification :fire: University of Maryland ICML 2022 [PUB] [PDF] [CODE]
Anarchic Federated Learning The Ohio State University ICML 2022 [PUB] [PDF]
QSFL: A Two-Level Uplink Communication Optimization Framework for Federated Learning Nankai University ICML 2022 [PUB] [CODE]
Bitwidth Heterogeneous Federated Learning with Progressive Weight Dequantization KAIST ICML 2022 [PUB] [PDF]
Neural Tangent Kernel Empowered Federated Learning NC State University ICML 2022 [PUB] [PDF] [CODE]
Understanding Clipping for Federated Learning: Convergence and Client-Level Differential Privacy UMN ICML 2022 [PUB] [PDF]
Personalized Federated Learning via Variational Bayesian Inference CAS ICML 2022 [PUB] [PDF] [SLIDE] [UC.]
Federated Learning with Label Distribution Skew via Logits Calibration ZJU ICML 2022 [PUB]
Neurotoxin: Durable Backdoors in Federated Learning Southeast University;Princeton ICML 2022 [PUB] [PDF] [CODE]
Resilient and Communication Efficient Learning for Heterogeneous Federated Systems Michigan State University ICML 2022 [PUB]
Minibatch vs Local SGD with Shuffling: Tight Convergence Bounds and Beyond KAIST ICLR (oral) 2022 [PUB] [CODE]
Bayesian Framework for Gradient Leakage ETH Zurich ICLR 2022 [PUB] [PDF] [CODE]
Federated Learning from only unlabeled data with class-conditional-sharing clients The University of Tokyo; CUHK ICLR 2022 [PUB] [CODE]
FedChain: Chained Algorithms for Near-Optimal Communication Cost in Federated Learning CMU; University of Illinois at Urbana-Champaign; University of Washington ICLR 2022 [PUB] [PDF]
Acceleration of Federated Learning with Alleviated Forgetting in Local Training THU ICLR 2022 [PUB] [PDF] [CODE]
FedPara: Low-rank Hadamard Product for Communicatkion-Efficient Federated Learning POSTECH ICLR 2022 [PUB] [PDF] [CODE]
An Agnostic Approach to Federated Learning with Class Imbalance University of Pennsylvania ICLR 2022 [PUB] [CODE]
Efficient Split-Mix Federated Learning for On-Demand and In-Situ Customization Michigan State University; The University of Texas at Austin ICLR 2022 [PUB] [PDF] [CODE]
Robbing the Fed: Directly Obtaining Private Data in Federated Learning with Modified Models :fire: University of Maryland; NYU ICLR 2022 [PUB] [PDF] [CODE]
ZeroFL: Efficient On-Device Training for Federated Learning with Local Sparsity University of Cambridge; University of Oxford ICLR 2022 [PUB] [PDF]
Diverse Client Selection for Federated Learning via Submodular Maximization Intel; CMU ICLR 2022 [PUB] [CODE]
Recycling Model Updates in Federated Learning: Are Gradient Subspaces Low-Rank? Purdue ICLR 2022 [PUB] [PDF] [CODE]
Diurnal or Nocturnal? Federated Learning of Multi-branch Networks from Periodically Shifting Distributions :fire: University of Maryland; Google ICLR 2022 [PUB] [CODE]
Towards Model Agnostic Federated Learning Using Knowledge Distillation EPFL ICLR 2022 [PUB] [PDF] [CODE]
Divergence-aware Federated Self-Supervised Learning NTU; SenseTime ICLR 2022 [PUB] [PDF] [CODE]
What Do We Mean by Generalization in Federated Learning? :fire: Stanford; Google ICLR 2022 [PUB] [PDF] [CODE]
FedBABU: Toward Enhanced Representation for Federated Image Classification KAIST ICLR 2022 [PUB] [PDF] [CODE]
Byzantine-Robust Learning on Heterogeneous Datasets via Bucketing EPFL ICLR 2022 [PUB] [PDF] [CODE]
Improving Federated Learning Face Recognition via Privacy-Agnostic Clusters Aibee ICLR Spotlight 2022 [PUB] [PDF] [PAGE] [解读]
Hybrid Local SGD for Federated Learning with Heterogeneous Communications University of Texas; Pennsylvania State University ICLR 2022 [PUB]
On Bridging Generic and Personalized Federated Learning for Image Classification The Ohio State University ICLR 2022 [PUB] [PDF] [CODE]
Minibatch vs Local SGD with Shuffling: Tight Convergence Bounds and Beyond KAIST; MIT ICLR 2022 [PUB] [PDF]
One-Shot Federated Learning: Theoretical Limits and Algorithms to Achieve Them. JMLR 2021 [PUB] [CODE]
Constrained differentially private federated learning for low-bandwidth devices UAI 2021 [PUB] [PDF]
Federated stochastic gradient Langevin dynamics UAI 2021 [PUB] [PDF]
Federated Learning Based on Dynamic Regularization BU; ARM ICLR 2021 [PUB] [PDF] [CODE]
Achieving Linear Speedup with Partial Worker Participation in Non-IID Federated Learning The Ohio State University ICLR 2021 [PUB] [PDF]
HeteroFL: Computation and Communication Efficient Federated Learning for Heterogeneous Clients Duke University ICLR 2021 [PUB] [PDF] [CODE]
FedMix: Approximation of Mixup under Mean Augmented Federated Learning KAIST ICLR 2021 [PUB] [PDF]
Federated Learning via Posterior Averaging: A New Perspective and Practical Algorithms :fire: CMU; Google ICLR 2021 [PUB] [PDF] [CODE]
Adaptive Federated Optimization :fire: Google ICLR 2021 [PUB] [PDF] [CODE]
Personalized Federated Learning with First Order Model Optimization Stanford; NVIDIA ICLR 2021 [PUB] [PDF] [CODE] [UC.]
FedBN: Federated Learning on Non-IID Features via Local Batch Normalization :fire: Princeton ICLR 2021 [PUB] [PDF] [CODE]
FedBE: Making Bayesian Model Ensemble Applicable to Federated Learning The Ohio State University ICLR 2021 [PUB] [PDF] [CODE]
Federated Semi-Supervised Learning with Inter-Client Consistency & Disjoint Learning KAIST ICLR 2021 [PUB] [PDF] [CODE]
KD3A: Unsupervised Multi-Source Decentralized Domain Adaptation via Knowledge Distillation ZJU ICML 2021 [PUB] [PDF] [CODE] [解读]
Gradient Disaggregation: Breaking Privacy in Federated Learning by Reconstructing the User Participant Matrix Harvard University ICML 2021 [PUB] [PDF] [VIDEO] [CODE]
FL-NTK: A Neural Tangent Kernel-based Framework for Federated Learning Analysis PKU; Princeton ICML 2021 [PUB] [PDF] [VIDEO]
Personalized Federated Learning using Hypernetworks :fire: Bar-Ilan University; NVIDIA ICML 2021 [PUB] [PDF] [CODE] [PAGE] [VIDEO] [解读]
Federated Composite Optimization Stanford; Google ICML 2021 [PUB] [PDF] [CODE] [VIDEO] [SLIDE]
Exploiting Shared Representations for Personalized Federated Learning University of Texas at Austin; University of Pennsylvania ICML 2021 [PUB] [PDF] [CODE] [VIDEO]
Data-Free Knowledge Distillation for Heterogeneous Federated Learning :fire: Michigan State University ICML 2021 [PUB] [PDF] [CODE] [VIDEO]
Federated Continual Learning with Weighted Inter-client Transfer KAIST ICML 2021 [PUB] [PDF] [CODE] [VIDEO]
Federated Deep AUC Maximization for Hetergeneous Data with a Constant Communication Complexity The University of Iowa ICML 2021 [PUB] [PDF] [CODE] [VIDEO]
Bias-Variance Reduced Local SGD for Less Heterogeneous Federated Learning The University of Tokyo ICML 2021 [PUB] [PDF] [VIDEO]
Federated Learning of User Verification Models Without Sharing Embeddings Qualcomm ICML 2021 [PUB] [PDF] [VIDEO]
Clustered Sampling: Low-Variance and Improved Representativity for Clients Selection in Federated Learning Accenture ICML 2021 [PUB] [PDF] [CODE] [VIDEO]
Ditto: Fair and Robust Federated Learning Through Personalization CMU; Facebook AI ICML 2021 [PUB] [PDF] [CODE] [VIDEO]
Heterogeneity for the Win: One-Shot Federated Clustering CMU ICML 2021 [PUB] [PDF] [VIDEO]
The Distributed Discrete Gaussian Mechanism for Federated Learning with Secure Aggregation :fire: Google ICML 2021 [PUB] [PDF] [CODE] [VIDEO]
Debiasing Model Updates for Improving Personalized Federated Training BU; Arm ICML 2021 [PUB] [CODE] [VIDEO]
One for One, or All for All: Equilibria and Optimality of Collaboration in Federated Learning Toyota; Berkeley; Cornell University ICML 2021 [PUB] [PDF] [CODE] [VIDEO]
CRFL: Certifiably Robust Federated Learning against Backdoor Attacks UIUC; IBM ICML 2021 [PUB] [PDF] [CODE] [VIDEO]
Federated Learning under Arbitrary Communication Patterns Indiana University; Amazon ICML 2021 [PUB] [VIDEO]
CANITA: Faster Rates for Distributed Convex Optimization with Communication Compression CMU NeurIPS 2021 [PUB] [PDF]
Boosting with Multiple Sources Google NeurIPS 2021 [PUB]
DRIVE: One-bit Distributed Mean Estimation VMware NeurIPS 2021 [PUB] [CODE]
Gradient Driven Rewards to Guarantee Fairness in Collaborative Machine Learning NUS NeurIPS 2021 [PUB] [CODE]
Gradient Inversion with Generative Image Prior POSTECH NeurIPS 2021 [PUB] [PDF] [CODE]
Distributed Machine Learning with Sparse Heterogeneous Data University of Oxford NeurIPS 2021 [PUB] [PDF]
Renyi Differential Privacy of The Subsampled Shuffle Model In Distributed Learning UCLA NeurIPS 2021 [PUB] [PDF]
Sageflow: Robust Federated Learning against Both Stragglers and Adversaries KAIST NeurIPS 2021 [PUB]
CAFE: Catastrophic Data Leakage in Vertical Federated Learning Rensselaer Polytechnic Institute; IBM Research NeurIPS 2021 [PUB] [CODE]
Fault-Tolerant Federated Reinforcement Learning with Theoretical Guarantee NUS NeurIPS 2021 [PUB] [PDF] [CODE]
Optimality and Stability in Federated Learning: A Game-theoretic Approach Cornell University NeurIPS 2021 [PUB] [PDF] [CODE]
QuPeD: Quantized Personalization via Distillation with Applications to Federated Learning UCLA NeurIPS 2021 [PUB] [PDF] [CODE] [解读]
The Skellam Mechanism for Differentially Private Federated Learning :fire: Google Research; CMU NeurIPS 2021 [PUB] [PDF] [CODE]
No Fear of Heterogeneity: Classifier Calibration for Federated Learning with Non-IID Data NUS; Huawei NeurIPS 2021 [PUB] [PDF]
STEM: A Stochastic Two-Sided Momentum Algorithm Achieving Near-Optimal Sample and Communication Complexities for Federated Learning UMN NeurIPS 2021 [PUB] [PDF]
Subgraph Federated Learning with Missing Neighbor Generation Emory; UBC; Lehigh University NeurIPS 2021 [PUB] [PDF] [CODE] [解读]
Evaluating Gradient Inversion Attacks and Defenses in Federated Learning :fire: Princeton NeurIPS 2021 [PUB] [PDF] [CODE]
Personalized Federated Learning With Gaussian Processes Bar-Ilan University NeurIPS 2021 [PUB] [PDF] [CODE]
Differentially Private Federated Bayesian Optimization with Distributed Exploration MIT; NUS NeurIPS 2021 [PUB] [PDF] [CODE]
Parameterized Knowledge Transfer for Personalized Federated Learning PolyU NeurIPS 2021 [PUB] [PDF] [CODE]
Federated Reconstruction: Partially Local Federated Learning :fire: Google Research NeurIPS 2021 [PUB] [PDF] [CODE] [UC.]
Fast Federated Learning in the Presence of Arbitrary Device Unavailability THU; Princeton; MIT NeurIPS 2021 [PUB] [PDF] [CODE]
FL-WBC: Enhancing Robustness against Model Poisoning Attacks in Federated Learning from a Client Perspective Duke University; Accenture Labs NeurIPS 2021 [PUB] [PDF] [CODE]
FjORD: Fair and Accurate Federated Learning under heterogeneous targets with Ordered Dropout KAUST; Samsung AI Center NeurIPS 2021 [PUB] [PDF]
Linear Convergence in Federated Learning: Tackling Client Heterogeneity and Sparse Gradients University of Pennsylvania NeurIPS 2021 [PUB] [PDF] [VIDEO]
Federated Multi-Task Learning under a Mixture of Distributions INRIA; Accenture Labs NeurIPS 2021 [PUB] [PDF] [CODE]
Federated Graph Classification over Non-IID Graphs Emory NeurIPS 2021 [PUB] [PDF] [CODE] [解读]
Federated Hyperparameter Tuning: Challenges, Baselines, and Connections to Weight-Sharing CMU; Hewlett Packard Enterprise NeurIPS 2021 [PUB] [PDF] [CODE]
On Large-Cohort Training for Federated Learning :fire: Google; CMU NeurIPS 2021 [PUB] [PDF] [CODE]
DeepReduce: A Sparse-tensor Communication Framework for Federated Deep Learning KAUST; Columbia University; University of Central Florida NeurIPS 2021 [PUB] [PDF] [CODE]
PartialFed: Cross-Domain Personalized Federated Learning via Partial Initialization Huawei NeurIPS 2021 [PUB] [VIDEO]
Federated Split Task-Agnostic Vision Transformer for COVID-19 CXR Diagnosis KAIST NeurIPS 2021 [PUB] [PDF]
Addressing Algorithmic Disparity and Performance Inconsistency in Federated Learning THU; Alibaba; Weill Cornell Medicine NeurIPS 2021 [PUB] [PDF] [CODE]
Federated Linear Contextual Bandits The Pennsylvania State University; Facebook; University of Virginia NeurIPS 2021 [PUB] [PDF] [CODE]
Few-Round Learning for Federated Learning KAIST NeurIPS 2021 [PUB]
Breaking the centralized barrier for cross-device federated learning EPFL; Google Research NeurIPS 2021 [PUB] [CODE] [VIDEO]
Federated-EM with heterogeneity mitigation and variance reduction Ecole Polytechnique; Google Research NeurIPS 2021 [PUB] [PDF]
Delayed Gradient Averaging: Tolerate the Communication Latency for Federated Learning MIT; Amazon; Google NeurIPS 2021 [PUB] [PAGE] [SLIDE]
FedDR – Randomized Douglas-Rachford Splitting Algorithms for Nonconvex Federated Composite Optimization University of North Carolina at Chapel Hill; IBM Research NeurIPS 2021 [PUB] [PDF] [CODE]
Federated Adversarial Domain Adaptation BU; Columbia University; Rutgers University ICLR 2020 [PUB] [PDF] [CODE]
DBA: Distributed Backdoor Attacks against Federated Learning ZJU; IBM Research ICLR 2020 [PUB] [CODE]
Fair Resource Allocation in Federated Learning :fire: CMU; Facebook AI ICLR 2020 [PUB] [PDF] [CODE]
Federated Learning with Matched Averaging :fire: University of Wisconsin-Madison; IBM Research ICLR 2020 [PUB] [PDF] [CODE]
Differentially Private Meta-Learning CMU ICLR 2020 [PUB] [PDF]
Generative Models for Effective ML on Private, Decentralized Datasets :fire: Google ICLR 2020 [PUB] [PDF] [CODE]
On the Convergence of FedAvg on Non-IID Data :fire: PKU ICLR 2020 [PUB] [PDF] [CODE] [解读]
FedBoost: A Communication-Efficient Algorithm for Federated Learning Google ICML 2020 [PUB] [VIDEO]
FetchSGD: Communication-Efficient Federated Learning with Sketching UC Berkeley; Johns Hopkins University; Amazon ICML 2020 [PUB] [PDF] [VIDEO] [CODE]
SCAFFOLD: Stochastic Controlled Averaging for Federated Learning EPFL; Google ICML 2020 [PUB] [PDF] [VIDEO] [UC.] [解读]
Federated Learning with Only Positive Labels Google ICML 2020 [PUB] [PDF] [VIDEO]
From Local SGD to Local Fixed-Point Methods for Federated Learning Moscow Institute of Physics and Technology; KAUST ICML 2020 [PUB] [PDF] [SLIDE] [VIDEO]
Acceleration for Compressed Gradient Descent in Distributed and Federated Optimization KAUST ICML 2020 [PUB] [PDF] [SLIDE] [VIDEO]
Differentially-Private Federated Linear Bandits MIT NeurIPS 2020 [PUB] [PDF] [CODE]
Federated Principal Component Analysis University of Cambridge; Quine Technologies NeurIPS 2020 [PUB] [PDF] [CODE]
FedSplit: an algorithmic framework for fast federated optimization UC Berkeley NeurIPS 2020 [PUB] [PDF]
Federated Bayesian Optimization via Thompson Sampling NUS; MIT NeurIPS 2020 [PUB] [PDF] [CODE]
Lower Bounds and Optimal Algorithms for Personalized Federated Learning KAUST NeurIPS 2020 [PUB] [PDF]
Robust Federated Learning: The Case of Affine Distribution Shifts UC Santa Barbara; MIT NeurIPS 2020 [PUB] [PDF] [CODE]
An Efficient Framework for Clustered Federated Learning UC Berkeley; DeepMind NeurIPS 2020 [PUB] [PDF] [CODE]
Distributionally Robust Federated Averaging :fire: Pennsylvania State University NeurIPS 2020 [PUB] [PDF] [CODE]
Personalized Federated Learning with Moreau Envelopes :fire: The University of Sydney NeurIPS 2020 [PUB] [PDF] [CODE]
Personalized Federated Learning with Theoretical Guarantees: A Model-Agnostic Meta-Learning Approach MIT; UT Austin NeurIPS 2020 [PUB] [PDF] [UC.]
Group Knowledge Transfer: Federated Learning of Large CNNs at the Edge USC NeurIPS 2020 [PUB] [PDF] [CODE] [解读]
Tackling the Objective Inconsistency Problem in Heterogeneous Federated Optimization :fire: CMU; Princeton NeurIPS 2020 [PUB] [PDF] [CODE] [UC.]
Attack of the Tails: Yes, You Really Can Backdoor Federated Learning University of Wisconsin-Madison NeurIPS 2020 [PUB] [PDF]
Federated Accelerated Stochastic Gradient Descent Stanford NeurIPS 2020 [PUB] [PDF] [CODE] [VIDEO]
Inverting Gradients - How easy is it to break privacy in federated learning? :fire: University of Siegen NeurIPS 2020 [PUB] [PDF] [CODE]
Ensemble Distillation for Robust Model Fusion in Federated Learning EPFL NeurIPS 2020 [PUB] [PDF] [CODE]
Throughput-Optimal Topology Design for Cross-Silo Federated Learning INRIA NeurIPS 2020 [PUB] [PDF] [CODE]
Bayesian Nonparametric Federated Learning of Neural Networks :fire: IBM ICML 2019 [PUB] [PDF] [CODE]
Analyzing Federated Learning through an Adversarial Lens :fire: Princeton; IBM ICML 2019 [PUB] [PDF] [CODE]
Agnostic Federated Learning Google ICML 2019 [PUB] [PDF]
cpSGD: Communication-efficient and differentially-private distributed SGD Princeton; Google NeurIPS 2018 [PUB] [PDF]
Federated Multi-Task Learning :fire: Stanford; USC; CMU NeurIPS 2017 [PUB] [PDF] [CODE]

联邦学习在顶级数据挖掘会议和期刊中

被顶级数据挖掘（Data Mining, DM）会议和期刊收录的联邦学习论文，包括 KDD（ACM SIGKDD 知识发现与数据挖掘会议）和 WSDM（Web 搜索与数据挖掘会议）。

联邦学习在顶级数据挖掘会议和期刊中
Title Affiliation Venue Year Materials
Asymmetrical Reciprocity-based Federated Learning for Resolving Disparities in Medical Diagnosis KDD 2025 [PUB]
Task Diversity in Bayesian Federated Learning: Simultaneous Processing of Classification and Regression KDD 2025 [PUB]
Runtime-Aware Pipeline for Vertical Federated Learning with Bounded Model Staleness KDD 2025 [PUB]
FLMarket: Enabling Privacy-preserved Pre-training Data Pricing for Federated Learning KDD 2025 [PUB]
Breaking the Memory Wall for Heterogeneous Federated Learning via Progressive Training KDD 2025 [PUB]
PraFFL: A Preference-Aware Scheme in Fair Federated Learning KDD 2025 [PUB]
Generalizing Personalized Federated Graph Augmentation via Min-max Adversarial Learning KDD 2025 [PUB]
BTFL: A Bayesian-based Test-Time Generalization Method for Internal and External Data Distributions in Federated learning KDD 2025 [PUB]
Privacy-Preserving Orthogonal Aggregation for Guaranteeing Gender Fairness in Federated Recommendation WSDM 2025 [PUB]
FedGF: Enhancing Structural Knowledge via Graph Factorization for Federated Graph Learning WSDM 2025 [PUB]
Towards Personalized Federated Multi-Scenario Multi-Task Recommendation WSDM 2025 [PUB]
Density-aware and Cluster-based Federated Anomaly Detection on Data Streams WSDM 2025 [PUB]
Integrating Knowledge Graphs and Neuro-Symbolic AI: LDM Enables FAIR and Federated Research Data Management WSDM 2025 [PUB]
FedKDD: International Joint Workshop on Federated Learning for Data Mining and Graph Analytics KDD Workshop 2024 [PUB]
Is Aggregation the Only Choice? Federated Learning via Layer-wise Model Recombination KDD 2024 [PUB]
BadSampler: Harnessing the Power of Catastrophic Forgetting to Poison Byzantine-robust Federated Learning KDD 2024 [PUB]
Federated Graph Learning with Structure Proxy Alignment KDD 2024 [PUB]
HiFGL: A Hierarchical Framework for Cross-silo Cross-device Federated Graph Learning KDD 2024 [PUB]
FedSecurity: A Benchmark for Attacks and Defenses in Federated Learning and Federated LLMs KDD 2024 [PUB]
Distributed Harmonization: Federated Clustered Batch Effect Adjustment and Generalization KDD 2024 [PUB]
FederatedScope-LLM: A Comprehensive Package for Fine-tuning Large Language Models in Federated Learning KDD 2024 [PUB]
On the Convergence of Zeroth-Order Federated Tuning for Large Language Models KDD 2024 [PUB]
CASA: Clustered Federated Learning with Asynchronous Clients KDD 2024 [PUB]
FLAIM: AIM-based Synthetic Data Generation in the Federated Setting KDD 2024 [PUB]
Privacy-Preserving Federated Learning using Flower Framework KDD 2024 [PUB]
FedSAC: Dynamic Submodel Allocation for Collaborative Fairness in Federated Learning KDD 2024 [PUB]
FedNLR: Federated Learning with Neuron-wise Learning Rates KDD 2024 [PUB]
FedBiOT: LLM Local Fine-tuning in Federated Learning without Full Model KDD 2024 [PUB]
FLea: Addressing Data Scarcity and Label Skew in Federated Learning via Privacy-preserving Feature Augmentation KDD 2024 [PUB]
Preventing Strategic Behaviors in Collaborative Inference for Vertical Federated Learning KDD 2024 [PUB]
PeFAD: A Parameter-Efficient Federated Framework for Time Series Anomaly Detection KDD 2024 [PUB]
FedRoLA: Robust Federated Learning Against Model Poisoning via Layer-based Aggregation KDD 2024 [PUB]
FedGTP: Exploiting Inter-Client Spatial Dependency in Federated Graph-based Traffic Prediction KDD 2024 [PUB]
OpenFedLLM: Training Large Language Models on Decentralized Private Data via Federated Learning KDD 2024 [PUB]
Personalized Federated Continual Learning via Multi-Granularity Prompt KDD 2024 [PUB]
Enabling Collaborative Test-Time Adaptation in Dynamic Environment via Federated Learning KDD 2024 [PUB]
GPFedRec: Graph-Guided Personalization for Federated Recommendation KDD 2024 [PUB]
Asynchronous Vertical Federated Learning for Kernelized AUC Maximization KDD 2024 [PUB]
VertiMRF: Differentially Private Vertical Federated Data Synthesis KDD 2024 [PUB]
User Consented Federated Recommender System Against Personalized Attribute Inference Attack HKUST WSDM 2024 [PUB] [PDF] [CODE]
Guardian: Guarding against Gradient Leakage with Provable Defense for Federated Learning ECNU WSDM 2024 [PUB]
Privacy Matters: Vertical Federated Linear Contextual Bandits for Privacy Protected Recommendation University of Cambridge KDD 2023 [PUB] [PDF]
FedDefender: Client-Side Attack-Tolerant Federated Learning KAIST KDD 2023 [PUB] [PDF] [CODE]
FedAPEN: Personalized Cross-silo Federated Learning with Adaptability to Statistical Heterogeneity ZJU KDD 2023 [PUB] [CODE]
FedPseudo: Privacy-Preserving Pseudo Value-Based Deep Learning Models for Federated Survival Analysis UMBC KDD 2023 [PUB] [PDF]
ShapleyFL: Robust Federated Learning Based on Shapley Value ZJU KDD 2023 [PUB] [CODE]
Federated Few-shot Learning University of Virginia KDD 2023 [PUB] [PDF] [CODE]
Theoretical Convergence Guaranteed Resource-Adaptive Federated Learning with Mixed Heterogeneity SDU KDD 2023 [PUB]
Personalized Federated Learning with Parameter Propagation UIUC KDD 2023 [PUB]
Serverless Federated AUPRC Optimization for Multi-Party Collaborative Imbalanced Data Mining University of Pittsburgh KDD 2023 [PUB] [PDF] [CODE]
CriticalFL: A Critical Learning Periods Augmented Client Selection Framework for Efficient Federated Learning SUNY-Binghamton University KDD 2023 [PUB] [PDF]
FLAMES2Graph: An Interpretable Federated Multivariate Time Series Classification Framework L3S Research Center KDD 2023 [PUB] [PDF]
FedCP: Separating Feature Information for Personalized Federated Learning via Conditional Policy SJTU KDD 2023 [PUB] [PDF] [CODE]
Navigating Alignment for Non-identical Client Class Sets: A Label Name-Anchored Federated Learning Framework UCSD KDD 2023 [PUB] [PDF] [CODE]
DM-PFL: Hitchhiking Generic Federated Learning for Efficient Shift-Robust Personalization BUAA KDD 2023 [PUB] [CODE]
FS-REAL: Towards Real-World Cross-Device Federated Learning Alibaba Group KDD 2023 [PUB] [PDF]
FedMultimodal: A Benchmark for Multimodal Federated Learning USC KDD 2023 [PUB] [PDF] [CODE]
PrivateRec: Differentially Private Model Training and Online Serving for Federated News Recommendation RUC KDD 2023 [PUB] [PDF] [NEWS]
Revisiting Personalized Federated Learning: Robustness Against Backdoor Attacks HKUST; Alibaba Group KDD 2023 [PUB] [PDF] [CODE]
UA-FedRec: Untargeted Attack on Federated News Recommendation USTC KDD 2023 [PUB] [PDF] [CODE]
International Workshop on Federated Learning for Distributed Data Mining MSU KDD Workshop Summaries 2023 [PUB] [PAGE]
Is Normalization Indispensable for Multi-domain Federated Learning? KDD workshop 2023 [PUB]
Distributed Personalized Empirical Risk Minimization. KDD workshop 2023 [PUB]
Once-for-All Federated Learning: Learning From and Deploying to Heterogeneous Clients. KDD workshop 2023 [PUB]
SparseVFL: Communication-Efficient Vertical Federated Learning Based on Sparsification of Embeddings and Gradients. KDD workshop 2023 [PUB]
Optimization of User Resources in Federated Learning for Urban Sensing Applications KDD workshop 2023 [PUB]
FedLEGO: Enabling Heterogenous Model Cooperation via Brick Reassembly in Federated Learning. KDD workshop 2023 [PUB]
Federated Graph Analytics with Differential Privacy. KDD workshop 2023 [PUB]
Scaling Distributed Multi-task Reinforcement Learning with Experience Sharing. KDD workshop 2023 [PUB]
Uncertainty Quantification in Federated Learning for Heterogeneous Health Data KDD workshop 2023 [PUB]
A Systematic Evaluation of Federated Learning on Biomedical Natural Language Processing. KDD workshop 2023 [PUB]
Taming Heterogeneity to Deal with Test-Time Shift in Federated Learning. KDD workshop 2023 [PUB]
Federated Blood Supply Chain Demand Forecasting: A Case Study. KDD workshop 2023 [PUB]
Stochastic Clustered Federated Learning. KDD workshop 2023 [PUB]
A Privacy-Preserving Hybrid Federated Learning Framework for Financial Crime Detection. KDD workshop 2023 [PUB]
Exploring the Efficacy of Data-Decoupled Federated Learning for Image Classification and Medical Imaging Analysis. KDD workshop 2023 [PUB]
FedNoisy: A Federated Noisy Label Learning Benchmark KDD workshop 2023 [PUB]
Asynchronous Decentralized Federated Lifelong Learning for Landmark Localization in Medical Imaging KDD workshop 2023 [PUB]
Federated learning for competing risk analysis in healthcare. KDD workshop 2023 [PUB]
Federated Threat Detection for Smart Home IoT rules. KDD workshop 2023 [PUB]
Federated Unlearning for On-Device Recommendation UQ WSDM 2023 [PUB] [PDF]
Collaboration Equilibrium in Federated Learning THU KDD 2022 [PUB] [PDF] [CODE]
Connected Low-Loss Subspace Learning for a Personalization in Federated Learning Ulsan National Institute of Science and Technology KDD 2022 [PUB] [PDF] [CODE]
FedMSplit: Correlation-Adaptive Federated Multi-Task Learning across Multimodal Split Networks University of Virginia KDD 2022 [PUB]
Communication-Efficient Robust Federated Learning with Noisy Labels University of Pittsburgh KDD 2022 [PUB] [PDF]
FLDetector: Detecting Malicious Clients in Federated Learning via Checking Model-Updates Consistency USTC KDD 2022 [PUB] [PDF] [CODE]
Practical Lossless Federated Singular Vector Decomposition Over Billion-Scale Data HKUST KDD 2022 [PUB] [PDF] [CODE]
FedWalk: Communication Efficient Federated Unsupervised Node Embedding with Differential Privacy SJTU KDD 2022 [PUB] [PDF]
FederatedScope-GNN: Towards a Unified, Comprehensive and Efficient Platform for Federated Graph Learning :fire: Alibaba KDD (Best Paper Award) 2022 [PUB] [PDF] [CODE]
Fed-LTD: Towards Cross-Platform Ride Hailing via Federated Learning to Dispatch BUAA KDD 2022 [PUB] [PDF] [解读]
Felicitas: Federated Learning in Distributed Cross Device Collaborative Frameworks USTC KDD 2022 [PUB] [PDF]
No One Left Behind: Inclusive Federated Learning over Heterogeneous Devices Renmin University of China KDD 2022 [PUB] [PDF]
FedAttack: Effective and Covert Poisoning Attack on Federated Recommendation via Hard Sampling THU KDD 2022 [PUB] [PDF] [CODE]
PipAttack: Poisoning Federated Recommender Systems for Manipulating Item Promotion The University of Queensland WSDM 2022 [PUB] [PDF]
Fed2: Feature-Aligned Federated Learning George Mason University; Microsoft; University of Maryland KDD 2021 [PUB] [PDF]
FedRS: Federated Learning with Restricted Softmax for Label Distribution Non-IID Data Nanjing University KDD 2021 [PUB] [CODE]
Federated Adversarial Debiasing for Fair and Trasnferable Representations Michigan State University KDD 2021 [PUB] [PAGE] [CODE] [SLIDE]
Cross-Node Federated Graph Neural Network for Spatio-Temporal Data Modeling USC KDD 2021 [PUB] [CODE] [解读]
AsySQN: Faster Vertical Federated Learning Algorithms with Better Computation Resource Utilization Xidian University;JD Tech KDD 2021 [PUB] [PDF]
FLOP: Federated Learning on Medical Datasets using Partial Networks Duke University KDD 2021 [PUB] [PDF] [CODE]
A Practical Federated Learning Framework for Small Number of Stakeholders ETH Zürich WSDM 2021 [PUB] [CODE]
Federated Deep Knowledge Tracing USTC WSDM 2021 [PUB] [CODE]
FedFast: Going Beyond Average for Faster Training of Federated Recommender Systems University College Dublin KDD 2020 [PUB] [VIDEO]
Federated Doubly Stochastic Kernel Learning for Vertically Partitioned Data JD Tech KDD 2020 [PUB] [PDF] [VIDEO]
Federated Online Learning to Rank with Evolution Strategies Facebook AI Research WSDM 2019 [PUB] [CODE]

联邦学习在顶级安全会议和期刊中

联邦学习相关论文已被顶级安全会议和期刊接收，包括 S&P（IEEE 安全与隐私研讨会）、CCS（计算机与通信安全会议）、USENIX Security（USENIX 安全研讨会）以及 NDSS（网络与分布式系统安全研讨会）。

联邦学习在顶级安全会议和期刊中
标题 机构 会议 年份 文献
并非所有边都同样稳健：评估基于排名的联邦学习的鲁棒性 S&P 2025 [PUB]
在聚类联邦学习中，有限拜占庭客户端下的实用投毒攻击 S&P 2025 [PUB]
一种用于实现隐私保护联邦学习的交互式框架：在大型语言模型上的实验 S&P Workshop 2025 [PUB]
智能交通系统中联邦学习的隐私保护双向认证协议 S&P Workshop 2025 [PUB]
FedTilt：迈向多层级公平且鲁棒的联邦学习 S&P Workshop 2025 [PUB]
用于增强语言模型联邦学习的隐私保护数据去重 NDSS 2025 [PUB]
Scale-MIA：通过潜在空间重建对安全联邦学习的可扩展模型反演攻击 NDSS 2025 [PUB] [CODE]
URVFL：针对垂直联邦学习的不可检测数据重构攻击 NDSS 2025 [PUB]
RAIFLE：利用对抗性数据操纵对基于交互的联邦学习进行重构攻击 NDSS 2025 [PUB] [CODE]
拜占庭鲁棒的去中心化联邦学习 CCS 2024 [PUB]
一个都不能少：探索用户画像与物品在针对联邦推荐系统的无目标攻击中的相互作用 CCS 2024 [PUB]
基于记录级个性化差分隐私的跨silos联邦学习。 CCS 2024 [PUB]
可采样的匿名聚合用于隐私保护的联邦数据分析 CCS 2024 [PUB]
Camel：在差分隐私洗牌模型下通信高效且恶意安全的联邦学习 CCS 2024 [PUB]
联邦图学习中的分布式后门攻击及认证防御 CCS 2024 [PUB]
基于RLWE同态加密的两层数据打包用于安全联邦学习。 CCS 2024 [PUB]
海报：利用一元编码和打乱来防御联邦学习中的源推断攻击。 CCS 2024 [PUB]
海报：使用私有跨组织数据协作实现端到端隐私保护的垂直联邦学习。 CCS 2024 [PUB]
FP-Fed：隐私保护的浏览器指纹识别联邦检测 NDSS 2024 [PUB]
FreqFed：基于频率分析的缓解联邦学习中投毒攻击的方法 NDSS 2024 [PUB]
联邦学习中隐蔽投毒攻击的自动对抗适应 NDSS 2024 [PUB]
CrowdGuard：联邦学习中的后门检测 NDSS 2024 [PUB]
保护跨silos联邦学习中的标签分布 S&P 2024 [PUB]
FLShield：一种基于验证的联邦学习框架，用于防御投毒攻击 S&P 2024 [PUB]
BadVFL：垂直联邦学习中的后门攻击 S&P 2024 [PUB]
SHERPA：面向未来网络的隐私保护联邦学习中可解释的鲁棒算法，用于防御数据投毒攻击 S&P 2024 [PUB]
Loki：通过模型操纵对联邦学习的大规模数据重构攻击 S&P 2024 [PUB]
LayerDBA：绕过联邦学习中基于相似性的防御机制 S&P Workshop 2024 [PUB]
海报：通过合成交互实现隐私保护的联邦推荐 S&P Workshop 2024 [PUB]
机密联邦学习的性能分析 S&P Workshop 2024 [PUB]
将隐私保护机制反过来用于攻击联邦学习 帕维亚大学 CCS 2023 [PUB] [PDF]
MESAS：抵御自适应攻击者的联邦学习投毒防御 维尔茨堡大学 CCS 2023 [PUB]
martFL：通过稳健且可验证的联邦学习架构实现以效用为导向的数据市场 清华大学 CCS 2023 [PUB] [PDF] [CODE]
揭示联邦学习中隐私与认证鲁棒性之间的联系，以抵抗投毒攻击 伊利诺伊大学厄巴纳-香槟分校 CCS 2023 [PUB] [PDF]
海报：在横向联邦学习中实现强公平性的可验证数据估值 国立成功大学 CCS 2023 [PUB]
海报：弥合信任鸿沟：联邦数据生态系统中的数据使用透明度 亚琛工业大学 CCS 2023 [PUB]
每一票都重要：基于排名的联邦学习训练以抵抗投毒攻击 马萨诸塞大学阿默斯特分校 USENIX Security 2023 [PUB] [PDF]
PrivateFL：通过个性化数据转换实现准确且差分隐私保护的联邦学习 约翰霍普金斯大学 USENIX Security 2023 [PUB] [CODE]
梯度混淆在联邦学习中会带来虚假的安全感 北卡罗来纳州立大学 USENIX Security 2023 [PUB] [PDF] [CODE]
FedVal：联邦学习中的不同好或不同坏 AI Sweden USENIX Security 2023 [PUB] [PDF] [CODE]
保护联邦敏感话题分类免受投毒攻击 IMDEA Networks Institute NDSS 2023 [PUB] [PDF] [CODE]
PPA：针对联邦学习的偏好画像攻击 南京理工大学 NDSS 2023 [PUB] [PDF]
将隐私保护机制反过来用于攻击联邦学习 帕维亚大学、代尔夫特理工大学、帕多瓦大学、拉德博德大学 CCS 2023 [PUB] [PDF] [CODE]
CERBERUS：探索联邦安全事件预测 伦敦大学学院 CCS 2022 [PUB] [PDF]
EIFFeL：确保联邦学习的完整性 威斯康星大学麦迪逊分校 CCS 2022 [PUB] [PDF]
通过模型不一致性逃避联邦学习中的安全聚合 SPRING Lab；EPFL CCS 2022 [PUB] [PDF] [CODE]
差分隐私下的联邦提升决策树 沃里克大学 CCS 2022 [PUB] [PDF] [CODE]
FedRecover：利用历史信息从联邦学习中的投毒攻击中恢复 杜克大学 S&P 2023 [PUB] [PDF]
可扩展且隐私保护的联邦主成分分析 EPFL；Tune Insight SA S&P 2023 [PUB] [PDF]
SafeFL：适合多方计算的隐私且鲁棒的联邦学习框架 达姆施塔特工业大学 S&P Workshop 2023 [PUB]
关于鲁棒联邦学习安全性评估的陷阱 马萨诸塞大学 S&P Workshop 2023 [PUB]
BayBFed：联邦学习的贝叶斯后门防御 达姆施塔特工业大学；UTSA S&P 2023 [PUB] [PDF]
3DFed：适用于联邦学习的自适应且可扩展的隐秘后门攻击框架 香港理工大学 S&P 2023 [PUB] [CODE]
RoFL：安全联邦学习的鲁棒性 苏黎世联邦理工学院 S&P 2023 [PUB] [PDF] [CODE]
Flamingo：多轮单服务器安全聚合，适用于隐私保护的联邦学习。 宾夕法尼亚大学 S&P 2023 [PUB] [CODE]
ELSA：适用于存在恶意参与者的联邦学习的安全聚合。 S&P 2023
私密、高效且准确：利用差分隐私保护多方学习训练的模型 复旦大学 S&P 2023 [PUB] [PDF]
重新回到起点：对生产环境联邦学习中投毒攻击的批判性评估 马萨诸塞大学 S&P 2022 [PUB] [VIDEO]
SIMC：以半诚实成本实现对恶意客户端安全的机器学习推理 微软研究院 USENIX Security 2022 [PUB] [PDF] [CODE] [VIDEO] [SUPP]
利用错误学习的困难性实现联邦学习中高效、差分隐私保护的安全聚合 佛蒙特大学 USENIX Security 2022 [PUB] [SLIDE] [VIDEO]
对垂直联邦学习的标签推断攻击 浙江大学 USENIX Security 2022 [PUB] [SLIDE] [CODE] [VIDEO]
FLAME：驯服联邦学习中的后门 达姆施塔特工业大学 USENIX Security 2022 [PUB] [SLIDE] [PDF] [VIDEO]
局部和中央差分隐私用于联邦学习的鲁棒性和隐私 纽约州立大学布法罗分校 NDSS 2022 [PUB] [PDF] [VIDEO] [UC.]
可解释的联邦Transformer日志学习用于云威胁取证 圣言大学 NDSS 2022 [PUB] [VIDEO] [UC.]
FedCRI：联邦移动网络风险情报 达姆施塔特工业大学 NDSS 2022 [PUB] [VIDEO]
DeepSight：通过深度模型检查缓解联邦学习中的后门攻击 达姆施塔特工业大学 NDSS 2022 [PUB] [PDF] [VIDEO]
联邦网络中的私密层次聚类 新加坡国立大学 CCS 2021 [PUB] [PDF]
FLTrust：通过信任引导实现拜占庭鲁棒的联邦学习 杜克大学 NDSS 2021 [PUB] [PDF] [CODE] [VIDEO] [SLIDE]
POSEIDON：隐私保护的联邦神经网络学习 EPFL NDSS 2021 [PUB] [VIDEO]
操控拜占庭：优化联邦学习中的模型投毒攻击与防御 马萨诸塞大学阿默斯特分校 NDSS 2021 [PUB] [CODE] [VIDEO]
SAFELearn：用于隐私保护联邦学习的安全聚合 达姆施塔特工业大学 S&P Workshop 2021 [PUB]
局部模型投毒攻击至拜占庭鲁棒的联邦学习 俄亥俄州立大学 USENIX Security 2020 [PUB] [PDF] [CODE] [VIDEO] [SLIDE]
使用区块链构建可靠且可问责的隐私保护联邦学习框架 堪萨斯大学 CCS（海报） 2019 [PUB]
IOTFLA：实施联邦学习的安全且隐私保护的智能家居架构 蒙特利尔魁北克大学 S&P Workshop 2019 [PUB]
深度学习的全面隐私分析：针对集中式和联邦学习的被动与主动白盒推理攻击：🔥 马萨诸塞大学阿默斯特分校 S&P 2019 [PUB] [VIDEO] [SLIDE] [CODE]
实用的安全聚合用于隐私保护的机器学习 Google CCS 2017 [PUB] [PDF] [解读] [UC.] [UC]

顶级计算机视觉会议和期刊中的联邦学习

被顶级计算机视觉（CV）会议和期刊接收的联邦学习论文，包括 CVPR（计算机视觉与模式识别）、ICCV（IEEE 国际计算机视觉会议）、ECCV（欧洲计算机视觉会议）、MM（ACM 国际多媒体会议）、IJCV（国际计算机视觉杂志）。

顶级计算机视觉会议和期刊中的联邦学习
Title Affiliation Venue Year Materials
Federated Learning with Domain Shift Eraser CVPR 2025 [PUB]
Beyond Local Sharpness: Communication-Efficient Global Sharpness-aware Minimization for Federated Learning CVPR 2025 [PUB] [CODE]
FedBiP: Heterogeneous One-Shot Federated Learning with Personalized Latent Diffusion Models CVPR 2025 [PUB] [CODE]
FedCS: Coreset Selection for Federated Learning CVPR 2025 [PUB]
AFL: A Single-Round Analytic Approach for Federated Learning with Pre-trained Models CVPR 2025 [PUB]
NoT: Federated Unlearning via Weight Negation CVPR 2025 [PUB]
Fortifying Federated Learning Towards Trustworthiness via Auditable Data Valuation and Verifiable Client Contribution CVPR 2025 [PUB]
Infighting in the Dark: Multi-Label Backdoor Attack in Federated Learning CVPR 2025 [PUB]
Mind the Gap: Confidence Discrepancy Can Guide Federated Semi-Supervised Learning Across Pseudo-Mismatch CVPR 2025 [PUB] [CODE]
Geometric Knowledge-Guided Localized Global Distribution Alignment for Federated Learning CVPR 2025 [PUB]
HistoFS: Non-IID Histopathologic Whole Slide Image Classification via Federated Style Transfer with RoI-Preserving CVPR 2025 [PUB] [COCE]
F^3OCUS - Federated Finetuning of Vision-Language Foundation Models with Optimal Client Layer Updating Strategy via Multi-objective Meta-Heuristics CVPR 2025 [PUB] [PAGE]
FedAWA: Adaptive Optimization of Aggregation Weights in Federated Learning Using Client Vectors CVPR 2025 [PUB]
FedSPA: Generalizable Federated Graph Learning under Homophily Heterogeneity CVPR 2025 [PUB] [CODE]
Population Normalization for Federated Learning CVPR 2025 [PUB]
Model Poisoning Attacks to Federated Learning via Multi-Round Consistency CVPR 2025 [PUB] [CODE]
dFLMoE: Decentralized Federated Learning via Mixture of Experts for Medical Data Analysis CVPR 2025 [PUB]
Detecting Backdoor Attacks in Federated Learning via Direction Alignment Inspection CVPR 2025 [PUB] [CODE]
A Simple Data Augmentation for Feature Distribution Skewed Federated Learning CVPR 2025 [PUB] [CODE]
Handling Spatial-Temporal Data Heterogeneity for Federated Continual Learning via Tail Anchor CVPR 2025 [PUB]
Subspace Constraint and Contribution Estimation for Heterogeneous Federated Learning CVPR 2025 [PUB] [CODE]
pFedMxF: Personalized Federated Class-Incremental Learning with Mixture of Frequency Aggregation CVPR 2025 [PUB]
FedCALM: Conflict-aware Layer-wise Mitigation for Selective Aggregation in Deeper Personalized Federated Learning CVPR 2025 [PUB]
Unlearning through Knowledge Overwriting: Reversible Federated Unlearning via Selective Sparse Adapter CVPR 2025 [PUB]
FedMIA: An Effective Membership Inference Attack Exploiting "All for One" Principle in Federated Learning CVPR 2025 [PUB] [CODE]
Patient-Level Anatomy Meets Scanning-Level Physics: Personalized Federated Low-Dose CT Denoising Empowered by Large Language Model CVPR 2025 [PUB]
Relation-Guided Versatile Regularization for Federated Semi-Supervised Learning IJCV 2025 [PUB]
DualFed: Enjoying both Generalization and Personalization in Federated Learning via Hierachical Representations MM 2024 [PUB]
One-shot-but-not-degraded Federated Learning MM 2024 [PUB]
Overcoming Spatial-Temporal Catastrophic Forgetting for Federated Class-Incremental Learning MM 2024 [PUB]
FedDEO: Description-Enhanced One-Shot Federated Learning with Diffusion Models MM 2024 [PUB]
Decoupling General and Personalized Knowledge in Federated Learning via Additive and Low-rank Decomposition MM 2024 [PUB]
CoAst: Validation-Free Contribution Assessment for Federated Learning based on Cross-Round Valuation MM 2024 [PUB]
Spatio-temporal Heterogeneous Federated Learning for Time Series Classification with Multi-view Orthogonal Training MM 2024 [PUB]
FedEvalFair: A Privacy-Preserving and Statistically Grounded Federated Fairness Evaluation Framework MM 2024 [PUB]
One-Shot Sequential Federated Learning for Non-IID Data by Enhancing Local Model Diversity MM 2024 [PUB]
FedSLS: Exploring Federated Aggregation in Saliency Latent Space MM 2024 [PUB]
Cluster-driven Personalized Federated Recommendation with Interest-aware Graph Convolution Network for Multimedia MM 2024 [PUB]
FedBCGD: Communication-Efficient Accelerated Block Coordinate Gradient Descent for Federated Learning MM 2024 [PUB]
Federated Morozov Regularization for Shortcut Learning in Privacy Preserving Learning with Watermarked Image Data MM 2024 [PUB]
Cross-Modal Meta Consensus for Heterogeneous Federated Learning MM 2024 [PUB]
Masked Random Noise for Communication-Efficient Federated Learning MM 2024 [PUB]
Heterogeneity-Aware Federated Deep Multi-View Clustering towards Diverse Feature Representations MM 2024 [PUB]
Adaptive Hierarchical Aggregation for Federated Object Detection MM 2024 [PUB]
FedCAFE: Federated Cross-Modal Hashing with Adaptive Feature Enhancement MM 2024 [PUB]
Federated Fuzzy C-means with Schatten-p Norm Minimization MM 2024 [PUB]
Towards Effective Federated Graph Anomaly Detection via Self-boosted Knowledge Distillation MM 2024 [PUB]
Physics-Driven Spectrum-Consistent Federated Learning for Palmprint Verification IJCV 2024 [PUB]
SKYMASK: Attack-Agnostic Robust Federated Learning with Fine-Grained Learnable Masks ECCV 2024 [PUB] [CODE]
FedHide: Federated Learning by Hiding in the Neighbors ECCV 2024 [PUB]
FedVAD: Enhancing Federated Video Anomaly Detection with GPT-Driven Semantic Distillation ECCV 2024 [PUB]
FedRA: A Random Allocation Strategy for Federated Tuning to Unleash the Power of Heterogeneous Clients ECCV 2024 [PUB]
Pick-a-Back: Selective Device-to-Device Knowledge Transfer in Federated Continual Learning ECCV 2024 [PUB]
Federated Learning with Local Openset Noisy Labels ECCV 2024 [PUB]
FedTSA: A Cluster-Based Two-Stage Aggregation Method for Model-Heterogeneous Federated Learning. ECCV 2024 [PUB]
Overcome Modal Bias in Multi-modal Federated Learning via Balanced Modality Selection ECCV 2024 [PUB]
BAFFLE: A Baseline of Backpropagation-Free Federated Learning ECCV 2024 [PUB]
PILoRA: Prototype Guided Incremental LoRA for Federated Class-Incremental Learning ECCV 2024 [PUB]
Fisher Calibration for Backdoor-Robust Heterogeneous Federated Learning ECCV 2024 [PUB]
Unlocking the Potential of Federated Learning: The Symphony of Dataset Distillation via Deep Generative Latents ECCV 2024 [PUB]
FedHARM: Harmonizing Model Architectural Diversity in Federated Learning ECCV 2024 [PUB]
SuperFedNAS: Cost-Efficient Federated Neural Architecture Search for On-device Inference. ECCV 2024 [PUB]
Personalized Federated Domain-Incremental Learning Based on Adaptive Knowledge Matching. ECCV 2024 [PUB]
Diffusion-Driven Data Replay: A Novel Approach to Combat Forgetting in Federated Class Continual Learning ECCV 2024 [PUB]
Towards Multi-modal Transformers in Federated Learning ECCV 2024 [PUB]
Local and Global Flatness for Federated Domain Generalization ECCV 2024 [PUB]
Feature Diversification and Adaptation for Federated Domain Generalization ECCV 2024 [PUB]
PFEDEDIT: Personalized Federated Learning via Automated Model Editing ECCV 2024 [PUB]
FedHCA2: Towards Hetero-Client Federated Multi-Task Learning SJTU CVPR 2024 [PUB] [SUPP] [PDF] [CODE]
Fair Federated Learning under Domain Skew with Local Consistency and Domain Diversity WHU CVPR 2024 [PUB] [PDF] [CODE]
Think Twice Before Selection: Federated Evidential Active Learning for Medical Image Analysis with Domain Shifts NWPU; HKUST CVPR 2024 [PUB] [SUPP] [PDF] [CODE]
FedMef: Towards Memory-efficient Federated Dynamic Pruning CUHK CVPR 2024 [PUB] [SUPP] [PDF]
Communication-Efficient Federated Learning with Accelerated Client Gradient SNU CVPR 2024 [PUB] [SUPP] [PDF] [CODE]
Revamping Federated Learning Security from a Defender's Perspective: A Unified Defense with Homomorphic Encrypted Data Space IITH CVPR 2024 [PUB] [SUPP] [CODE]
Adaptive Hyper-graph Aggregation for Modality-Agnostic Federated Learning TJUT CVPR 2024 [PUB] [SUPP] [CODE]
Towards Efficient Replay in Federated Incremental Learning HUST CVPR 2024 [PUB] [SUPP] [PDF]
Mixed-Precision Quantization for Federated Learning on Resource-Constrained Heterogeneous Devices UT CVPR 2024 [PUB] [SUPP] [PDF]
Data Valuation and Detections in Federated Learning NUS CVPR 2024 [PUB] [SUPP] [PDF] [CODE]
Decentralized Directed Collaboration for Personalized Federated Learning NJUST CVPR 2024 [PUB] [SUPP] [PDF]
Unlocking the Potential of Prompt-Tuning in Bridging Generalized and Personalized Federated Learning UBC CVPR 2024 [PUB] [SUPP] [PDF] [CODE]
Global and Local Prompts Cooperation via Optimal Transport for Federated Learning ShanghaiTech University CVPR 2024 [PUB] [SUPP] [PDF] [CODE]
Rethinking the Representation in Federated Unsupervised Learning with Non-IID Data ZJU CVPR 2024 [PUB] [SUPP] [PDF] [CODE]
Relaxed Contrastive Learning for Federated Learning SNU CVPR 2024 [PUB] [SUPP] [PDF] [CODE]
Leak and Learn: An Attacker's Cookbook to Train Using Leaked Data from Federated Learning Purdue University CVPR 2024 [PUB] [SUPP] [PDF] [VIDEO]
Traceable Federated Continual Learning BUPT CVPR 2024 [PUB] [SUPP] [CODE]
Federated Online Adaptation for Deep Stereo University of Bologna CVPR 2024 [PUB] [SUPP] [PDF] [CODE] [PAGE] [VIDEO]
Federated Generalized Category Discovery UniTn CVPR 2024 [PUB] [SUPP] [PDF] [CODE]
Efficiently Assemble Normalization Layers and Regularization for Federated Domain Generalization ND CVPR 2024 [PUB] [SUPP] [PDF] [CODE]
Text-Enhanced Data-free Approach for Federated Class-Incremental Learning Monash University CVPR 2024 [PUB] [SUPP] [PDF] [CODE]
PerAda: Parameter-Efficient Federated Learning Personalization with Generalization Guarantees UIUC; NVIDIA CVPR 2024 [PUB] [SUPP] [PDF] [CODE]
FedSOL: Stabilized Orthogonal Learning with Proximal Restrictions in Federated Learning KAIST CVPR 2024 [PUB] [SUPP] [PDF] [CODE]
FedUV: Uniformity and Variance for Heterogeneous Federated Learning UC Davis CVPR 2024 [PUB] [SUPP] [PDF]
FedAS: Bridging Inconsistency in Personalized Federated Learning WHU CVPR 2024 [PUB] [CODE]
FedSelect: Personalized Federated Learning with Customized Selection of Parameters for Fine-Tuning Lapis Labs CVPR 2024 [PUB] [SUPP] [PDF] [CODE]
Device-Wise Federated Network Pruning PITT CVPR 2024 [PUB] [SUPP]
Byzantine-robust Decentralized Federated Learning via Dual-domain Clustering and Trust Bootstrapping HNU; PolyU; AIRS CVPR 2024 [PUB] [SUPP]
DiPrompT: Disentangled Prompt Tuning for Multiple Latent Domain Generalization in Federated Learning HKUST; PolyU CVPR 2024 [PUB] [SUPP] [PDF]
An Upload-Efficient Scheme for Transferring Knowledge From a Server-Side Pre-trained Generator to Clients in Heterogeneous Federated Learning SJTU CVPR 2024 [PUB] [SUPP] [PDF] [CODE] [POSTER] [SLIDES]
An Aggregation-Free Federated Learning for Tackling Data Heterogeneity A* STAR CVPR 2024 [PUB] [SUPP] [PDF]
FLHetBench: Benchmarking Device and State Heterogeneity in Federated Learning BUAA; HKU CVPR 2024 [PUB] [SUPP] [CODE] [PAGE] [POSTER] [VIDEO]
Collaborative Visual Place Recognition through Federated Learning CVPR workshop 2024 [PUB] [SUPP] [PDF]
FedProK: Trustworthy Federated Class-Incremental Learning via Prototypical Feature Knowledge Transfer CVPR workshop 2024 [PUB] [SUPP] [PDF]
Federated Hyperparameter Optimization Through Reward-Based Strategies: Challenges and Insights CVPR workshop 2024 [PUB]
On the Efficiency of Privacy Attacks in Federated Learning CVPR workshop 2024 [PUB] [PDF]
FedCE: Personalized Federated Learning Method based on Clustering Ensembles BJTU MM 2023 [PUB]
FedVQA: Personalized Federated Visual Question Answering over Heterogeneous Scenes Leiden University MM 2023 [PUB]
Towards Fast and Stable Federated Learning: Confronting Heterogeneity via Knowledge Anchor XJTU MM 2023 [PUB] [PDF] [CODE]
Federated Deep Multi-View Clustering with Global Self-Supervision UESTC MM 2023 [PUB] [PDF]
FedAA: Using Non-sensitive Modalities to Improve Federated Learning while Preserving Image Privacy ZJU MM 2023 [PUB]
Prototype-guided Knowledge Transfer for Federated Unsupervised Cross-modal Hashing SDNU MM 2023 [PUB] [CODE]
Joint Local Relational Augmentation and Global Nash Equilibrium for Federated Learning with Non-IID Data ZJU MM 2023 [PUB] [PDF]
FedCD: A Classifier Debiased Federated Learning Framework for Non-IID Data BUPT MM 2023 [PUB]
Federated Learning with Label-Masking Distillation UCAS MM 2023 [PUB] [CODE]
Cross-Silo Prototypical Calibration for Federated Learning with Non-IID Data SDU MM 2023 [PUB] [PDF] [CODE]
A Four-Pronged Defense Against Byzantine Attacks in Federated Learning HUST MM 2023 [PUB] [PDF]
Client-Adaptive Cross-Model Reconstruction Network for Modality-Incomplete Multimodal Federated Learning CAS; Peng Cheng Laboratory; UCAS MM 2023 [PUB]
FedGH: Heterogeneous Federated Learning with Generalized Global Header NKU MM 2023 [PUB] [PDF] [CODE]
Cuing Without Sharing: A Federated Cued Speech Recognition Framework via Mutual Knowledge Distillation CUHK MM 2023 [PUB] [PDF] [CODE]
AffectFAL: Federated Active Affective Computing with Non-IID Data TJUT MM 2023 [PUB] [CODE]
Improving Federated Person Re-Identification through Feature-Aware Proximity and Aggregation SZU MM 2023 [PUB]
Towards Attack-tolerant Federated Learning via Critical Parameter Analysis KAIST ICCV 2023 [PUB] [PDF] [CODE] [SUPP]
Efficient Model Personalization in Federated Learning via Client-Specific Prompt Generation NTU; NVIDIA ICCV 2023 [PUB] [PDF] [SUPP]
Generative Gradient Inversion via Over-Parameterized Networks in Federated Learning A*STAR ICCV 2023 [PUB] [CODE] [SUPP]
GPFL: Simultaneously Learning Global and Personalized Feature Information for Personalized Federated Learning SJTU ICCV 2023 [PUB] [PDF] [CODE] [SUPP]
Workie-Talkie: Accelerating Federated Learning by Overlapping Computing and Communications via Contrastive Regularization University of Houston ICCV 2023 [PUB] [SUPP]
PGFed: Personalize Each Client's Global Objective for Federated Learning University of Pittsburgh ICCV 2023 [PUB] [PDF] [CODE] [SUPP]
FedPerfix: Towards Partial Model Personalization of Vision Transformers in Federated Learning UCF ICCV 2023 [PUB] [PDF] [CODE] [SUPP]
L-DAWA: Layer-wise Divergence Aware Weight Aggregation in Federated Self-Supervised Visual Representation Learning TCL AI Lab ICCV 2023 [PUB] [PDF] [SUPP]
FedPD: Federated Open Set Recognition with Parameter Disentanglement City University of Hong Kong ICCV 2023 [PUB] [CODE]
TARGET: Federated Class-Continual Learning via Exemplar-Free Distillation ETH Zurich; Sony AI ICCV 2023 [PUB] [PDF] [CODE]
Towards Instance-adaptive Inference for Federated Learning A*STAR ICCV 2023 [PUB] [PDF] [CODE]
Communication-efficient Federated Learning with Single-Step Synthetic Features Compressor for Faster Convergence SCU; Engineering Research Center of Machine Learning and Industry Intelligence ICCV 2023 [PUB] [PDF] [CODE]
zPROBE: Zero Peek Robustness Checks for Federated Learning Purdue University ICCV 2023 [PUB] [PDF] [SUPP]
ProtoFL: Unsupervised Federated Learning via Prototypical Distillation KakaoBank Corp. ICCV 2023 [PUB] [PDF]
MAS: Towards Resource-Efficient Federated Multiple-Task Learning Sony AI ICCV 2023 [PUB] [PDF] [CODE] [SUPP]
FSAR: Federated Skeleton-based Action Recognition with Adaptive Topology Structure and Knowledge Distillation PKU ICCV 2023 [PUB] [PDF] [SUPP]
When Do Curricula Work in Federated Learning? UCSD ICCV 2023 [PUB] [PDF] [SUPP]
Communication-Efficient Vertical Federated Learning with Limited Overlapping Samples Duke University ICCV 2023 [PUB] [PDF] [CODE]
Multi-Metrics Adaptively Identifies Backdoors in Federated Learning SCUT ICCV 2023 [PUB] [PDF] [CODE] [SUPP]
No Fear of Classifier Biases: Neural Collapse Inspired Federated Learning with Synthetic and Fixed Classifier ZJU ICCV 2023 [PUB] [PDF] [CODE] [SUPP]
FRAug: Tackling Federated Learning with Non-IID Features via Representation Augmentation Ludwig Maximilian University of Munich; Siemens Technology ICCV 2023 [PUB] [PDF] [SUPP]
Bold but Cautious: Unlocking the Potential of Personalized Federated Learning through Cautiously Aggressive Collaboration BUAA ICCV 2023 [PUB] [PDF] [CODE] [SUPP]
Global Balanced Experts for Federated Long-Tailed Learning CUHK-Shenzhen ICCV 2023 [PUB] [CODE] [SUPP]
Knowledge-Aware Federated Active Learning with Non-IID Data The University of Sydney ICCV 2023 [PUB] [PDF] [CODE] [SUPP]
Enhancing Privacy Preservation in Federated Learning via Learning Rate Perturbation BUPT ICCV 2023 [PUB] [SUPP]
Local or Global: Selective Knowledge Assimilation for Federated Learning with Limited Labels CMU ICCV 2023 [PUB] [PDF] [SUPP]
Federated Learning Over Images: Vertical Decompositions and Pre-Trained Backbones Are Difficult to Beat Rice University ICCV 2023 [PUB] [PDF] [CODE] [SUPP]
Robust Heterogeneous Federated Learning under Data Corruption WHU ICCV 2023 [PUB] [CODE] [SUPP]
Personalized Semantics Excitation for Federated Image Classification Tulane University ICCV 2023 [PUB] [CODE]
Reducing Training Time in Cross-Silo Federated Learning Using Multigraph Topology AIOZ ICCV 2023 [PUB] [PDF] [CODE] [SUPP]
Window-based Model Averaging Improves Generalization in Heterogeneous Federated Learning. Politecnico di Torino ICCV workshop 2023 [PUB] [PDF]
Experience Replay as an Effective Strategy for Optimizing Decentralized Federated Learning. University of Catania ICCV workshop 2023 [PUB]
FedRCIL: Federated Knowledge Distillation for Representation based Contrastive Incremental Learning. Centre for Research and Technology Hellas; University of West Attica ICCV workshop 2023 [PUB] [CODE]
FedLID: Self-Supervised Federated Learning for Leveraging Limited Image Data. Centre for Research and Technology Hellas; University of West Attica ICCV workshop 2023 [PUB]
Rethinking Federated Learning With Domain Shift: A Prototype View WHU CVPR 2023 [PUB] [CODE]
Class Balanced Adaptive Pseudo Labeling for Federated Semi-Supervised Learning ECNU CVPR 2023 [PUB] [CODE]
DaFKD: Domain-Aware Federated Knowledge Distillation HUST CVPR 2023 [PUB] [CODE]
The Resource Problem of Using Linear Layer Leakage Attack in Federated Learning Purdue University CVPR 2023 [PUB] [PDF]
FedSeg: Class-Heterogeneous Federated Learning for Semantic Segmentation ZJU CVPR 2023 [PUB]
On the Effectiveness of Partial Variance Reduction in Federated Learning With Heterogeneous Data DTU CVPR 2023 [PUB] [PDF]
Elastic Aggregation for Federated Optimization Meituan CVPR 2023 [PUB]
FedDM: Iterative Distribution Matching for Communication-Efficient Federated Learning UCLA CVPR 2023 [PUB] [PDF]
Adaptive Channel Sparsity for Federated Learning Under System Heterogeneity UM CVPR 2023 [PUB]
ScaleFL: Resource-Adaptive Federated Learning With Heterogeneous Clients GaTech CVPR 2023 [PUB] [CODE]
Reliable and Interpretable Personalized Federated Learning TJU CVPR 2023 [PUB]
Federated Domain Generalization With Generalization Adjustment SJTU CVPR 2023 [PUB] [CODE]
Make Landscape Flatter in Differentially Private Federated Learning THU CVPR 2023 [PUB] [PDF] [CODE]
Confidence-Aware Personalized Federated Learning via Variational Expectation Maximization KU Leuven CVPR 2023 [PUB] [PDF] [CODE]
STDLens: Model Hijacking-Resilient Federated Learning for Object Detection GaTech CVPR 2023 [PUB] [PDF] [CODE]
Re-Thinking Federated Active Learning Based on Inter-Class Diversity KAIST CVPR 2023 [PUB] [PDF] [CODE]
Learning Federated Visual Prompt in Null Space for MRI Reconstruction A*STAR CVPR 2023 [PUB] [PDF] [CODE]
Fair Federated Medical Image Segmentation via Client Contribution Estimation CUHK CVPR 2023 [PUB] [PDF] [CODE]
Federated Learning With Data-Agnostic Distribution Fusion NJU CVPR 2023 [PUB] [CODE]
How To Prevent the Poor Performance Clients for Personalized Federated Learning? CSU CVPR 2023 [PUB]
GradMA: A Gradient-Memory-Based Accelerated Federated Learning With Alleviated Catastrophic Forgetting ECNU CVPR 2023 [PUB] [PDF] [CODE]
Bias-Eliminating Augmentation Learning for Debiased Federated Learning NTU CVPR 2023 [PUB]
Federated Incremental Semantic Segmentation CAS; UCAS CVPR 2023 [PUB] [PDF] [CODE]
Asynchronous Federated Continual Learning University of Padova CVPR workshop 2023 [PUB] [PDF] [SILDES] [CODE]
Mixed Quantization Enabled Federated Learning To Tackle Gradient Inversion Attacks UMBC CVPR workshop 2023 [PUB] [CODE]
OpenFed: A Comprehensive and Versatile Open-Source Federated Learning Framework Meituan CVPR workshop 2023 [PUB] [PDF] [CODE]
Federated Learning in Non-IID Settings Aided by Differentially Private Synthetic Data utexas CVPR workshop 2023 [PUB] [SUPP] [PDF] [CODE]
TimelyFL: Heterogeneity-Aware Asynchronous Federated Learning With Adaptive Partial Training USC CVPR workshop 2023 [PUB] [PDF]
Many-Task Federated Learning: A New Problem Setting and a Simple Baseline utexas CVPR workshop 2023 [PUB] [CODE]
Confederated Learning: Going Beyond Centralization CAS; UCAS MM 2022 [PUB]
Few-Shot Model Agnostic Federated Learning WHU MM 2022 [PUB] [CODE]
Feeling Without Sharing: A Federated Video Emotion Recognition Framework Via Privacy-Agnostic Hybrid Aggregation TJUT MM 2022 [PUB]
FedLTN: Federated Learning for Sparse and Personalized Lottery Ticket Networks ECCV 2022 [PUB] [SUPP]
Auto-FedRL: Federated Hyperparameter Optimization for Multi-Institutional Medical Image Segmentation ECCV 2022 [PUB] [SUPP] [PDF] [CODE]
Improving Generalization in Federated Learning by Seeking Flat Minima Politecnico di Torino ECCV 2022 [PUB] [SUPP] [PDF] [CODE]
AdaBest: Minimizing Client Drift in Federated Learning via Adaptive Bias Estimation ECCV 2022 [PUB] [SUPP] [PDF] [CODE] [PAGE]
SphereFed: Hyperspherical Federated Learning ECCV 2022 [PUB] [SUPP] [PDF]
Federated Self-Supervised Learning for Video Understanding ECCV 2022 [PUB] [PDF] [CODE]
FedVLN: Privacy-Preserving Federated Vision-and-Language Navigation ECCV 2022 [PUB] [SUPP] [PDF] [CODE]
Addressing Heterogeneity in Federated Learning via Distributional Transformation ECCV 2022 [PUB] [CODE]
FedX: Unsupervised Federated Learning with Cross Knowledge Distillation KAIST ECCV 2022 [PUB] [SUPP] [PDF] [CODE]
Personalizing Federated Medical Image Segmentation via Local Calibration Xiamen University ECCV 2022 [PUB] [SUPP] [PDF] [CODE]
ATPFL: Automatic Trajectory Prediction Model Design Under Federated Learning Framework HIT CVPR 2022 [PUB]
Rethinking Architecture Design for Tackling Data Heterogeneity in Federated Learning Stanford CVPR 2022 [PUB] [SUPP] [PDF] [CODE] [VIDEO]
FedCorr: Multi-Stage Federated Learning for Label Noise Correction Singapore University of Technology and Design CVPR 2022 [PUB] [SUPP] [PDF] [CODE] [VIDEO]
FedCor: Correlation-Based Active Client Selection Strategy for Heterogeneous Federated Learning Duke University CVPR 2022 [PUB] [SUPP] [PDF]
Layer-Wised Model Aggregation for Personalized Federated Learning PolyU CVPR 2022 [PUB] [SUPP] [PDF]
Local Learning Matters: Rethinking Data Heterogeneity in Federated Learning University of Central Florida CVPR 2022 [PUB] [SUPP] [PDF] [CODE]
Federated Learning With Position-Aware Neurons Nanjing University CVPR 2022 [PUB] [SUPP] [PDF]
RSCFed: Random Sampling Consensus Federated Semi-Supervised Learning HKUST CVPR 2022 [PUB] [SUPP] [PDF] [CODE]
Learn From Others and Be Yourself in Heterogeneous Federated Learning Wuhan University CVPR 2022 [PUB] [CODE] [VIDEO]
Robust Federated Learning With Noisy and Heterogeneous Clients Wuhan University CVPR 2022 [PUB] [SUPP] [CODE]
ResSFL: A Resistance Transfer Framework for Defending Model Inversion Attack in Split Federated Learning Arizona State University CVPR 2022 [PUB] [SUPP] [PDF] [CODE]
FedDC: Federated Learning With Non-IID Data via Local Drift Decoupling and Correction National University of Defense Technology CVPR 2022 [PUB] [PDF] [CODE] [解读]
Federated Class-Incremental Learning CAS; Northwestern University; UTS CVPR 2022 [PUB] [PDF] [CODE]
Fine-Tuning Global Model via Data-Free Knowledge Distillation for Non-IID Federated Learning PKU; JD Explore Academy; The University of Sydney CVPR 2022 [PUB] [PDF]
Differentially Private Federated Learning With Local Regularization and Sparsification CAS CVPR 2022 [PUB] [PDF]
Auditing Privacy Defenses in Federated Learning via Generative Gradient Leakage University of Tennessee; Oak Ridge National Laboratory; Google Research CVPR 2022 [PUB] [PDF] [CODE] [VIDEO]
CD2-pFed: Cyclic Distillation-Guided Channel Decoupling for Model Personalization in Federated Learning SJTU CVPR 2022 [PUB] [PDF]
Closing the Generalization Gap of Cross-Silo Federated Medical Image Segmentation Univ. of Pittsburgh; NVIDIA CVPR 2022 [PUB] [PDF]
Adaptive Differential Filters for Fast and Communication-Efficient Federated Learning HHI CVPR workshop 2022 [PUB] [PDF] [SILDES] [VIDEO]
MPAF: Model Poisoning Attacks to Federated Learning Based on Fake Clients Duke University CVPR workshop 2022 [PUB] [PDF] [SILDES] [VIDEO]
Communication-Efficient Federated Data Augmentation on Non-IID Data UESTC CVPR workshop 2022 [PUB]
Does Federated Dropout Actually Work? Stanford CVPR workshop 2022 [PUB] [VIDEO]
FedIris: Towards More Accurate and Privacy-preserving Iris Recognition via Federated Template Communication USTC; CRIPAC; CASIA CVPR workshop 2022 [PUB] [SLIDES] [VIDEO]
Multi-Institutional Collaborations for Improving Deep Learning-Based Magnetic Resonance Image Reconstruction Using Federated Learning Johns Hopkins University CVPR 2021 [PUB] [PDF] [CODE]
Model-Contrastive Federated Learning :fire: NUS; UC Berkeley CVPR 2021 [PUB] [PDF] [CODE] [解读]
FedDG: Federated Domain Generalization on Medical Image Segmentation via Episodic Learning in Continuous Frequency Space :fire: CUHK CVPR 2021 [PUB] [PDF] [CODE]
Soteria: Provable Defense Against Privacy Leakage in Federated Learning From Representation Perspective Duke University CVPR 2021 [PUB] [PDF] [CODE]
Federated Learning for Non-IID Data via Unified Feature Learning and Optimization Objective Alignment PKU ICCV 2021 [PUB]
Ensemble Attention Distillation for Privacy-Preserving Federated Learning University at Buffalo ICCV 2021 [PUB] [PDF]
Collaborative Unsupervised Visual Representation Learning from Decentralized Data NTU; SenseTime ICCV 2021 [PUB] [PDF]
Joint Optimization in Edge-Cloud Continuum for Federated Unsupervised Person Re-identification NTU MM 2021 [PUB] [PDF]
Federated Visual Classification with Real-World Data Distribution MIT; Google ECCV 2020 [PUB] [PDF] [VIDEO]
InvisibleFL: Federated Learning over Non-Informative Intermediate Updates against Multimedia Privacy Leakages MM 2020 [PUB]
Performance Optimization of Federated Person Re-identification via Benchmark Analysis data. NTU MM 2020 [PUB] [PDF] [CODE] [解读]

联邦学习在顶级自然语言处理会议和期刊中

被顶级人工智能和自然语言处理会议及期刊收录的联邦学习论文，包括 ACL（计算语言学协会年会）、NAACL（北美计算语言学协会分会）、EMNLP（自然语言处理中的经验方法会议）以及 COLING（计算语言学国际会议）。

联邦学习在顶级自然语言处理会议和期刊中
标题 机构 会议/期刊 年份 文献
面向异构客户端的鲁棒高效联邦低秩适应 ACL 2025 [PUB]
FedEx-LoRA：大型语言模型联邦高效微调的精确聚合 ACL 2025 [PUB]
大型语言模型的联邦数据高效指令微调 ACL Findings 2025 [PUB]
FedDQC：大型语言模型联邦指令微调中的数据质量控制 ACL Findings 2025 [PUB]
通信高效的张量化大型语言模型联邦微调 ACL Findings 2025 [PUB]
FedLEKE：面向多客户端协作的联邦定位后编辑知识编辑 ACL Findings 2025 [PUB]
联邦学习中的梯度反演攻击：通过离散优化暴露文本数据。 COLING 2025 [PUB]
FedMKT：大小语言模型之间的联邦互惠知识迁移。 COLING 2025 [PUB]
联邦增量式命名实体识别。 COLING 2025 [PUB]
FedCSR：基于双对比学习的多平台跨域序列推荐联邦框架 COLING 2025 [PUB]
面向多产品问答的联邦检索增强生成 COLING (Industry) 2025 [PUB]
联邦学习系统中强差分隐私的无繁琐算法 EMNLP 2024 [PUB]
安全地使用私有数据学习：面向大型语言模型的联邦学习框架 EMNLP 2024 [PUB]
FEDKIM：自适应联邦知识注入医学基础模型 EMNLP 2024 [PUB]
基于费希尔信息的大型语言模型高效课程联邦学习 EMNLP 2024 [PUB]
异构LoRA用于设备端基础模型的联邦微调 EMNLP 2024 [PUB]
通过量化LoRA促进联邦学习中的数据与模型隐私 EMNLP Findings 2024 [PUB]
异构LoRA用于设备端基础模型的联邦微调 EMNLP Findings 2024 [PUB]
基于公平选择的联邦学习，实现对低资源印度语言的通用多语言仇恨言论检测 NAACL 2024 [PUB]
多模态原型驱动的开放词汇联邦学习 NAACL 2024 [PUB]
按照攻击者意愿导航？面向联邦学习下鲁棒具身智能体的构建 NAACL 2024 [PUB]
FedLFC：基于LoRA的语言家族聚类，迈向高效的联邦多语言建模。 NAACL Findings 2024 [PUB]
无梯度提示微调的文本分类个性化联邦学习。 NAACL Findings 2024 [PUB]
公共大型语言模型能否助力私有跨设备联邦学习？ NAACL Findings 2024 [PUB]
带有偏见的视觉-语言模型下的公平联邦学习 ACL Findings 2024 [PUB]
参数高效的提示微调与自适应优化结合的大语言模型联邦学习 奥本大学 EMNLP 2023 [PUB] [PDF] [代码]
情感与情绪感知的多模态投诉识别联邦元学习 帕特纳理工学院 EMNLP 2023 [PUB] [代码]
FedID：大规模预训练语言模型的联邦交互式蒸馏 横滨国立大学 EMNLP 2023 [PUB] [代码]
FedTherapist：通过联邦学习利用智能手机上用户生成的语言表达进行心理健康监测 KAIST EMNLP 2023 [PUB] [PDF]
连续联邦学习的协同重放样本选择 卡内基梅隆大学 EMNLP产业赛道 2023 [PUB] [PDF]
可调软提示是联邦学习中的信使 中山大学 EMNLP Findings 2023 [PUB] [PDF] [代码]
语义解析的联邦学习：任务定义、评估设置、新算法 俄亥俄州立大学 ACL 2023 [PUB] [PDF] [代码]
FEDLEGAL：首个面向法律NLP的真实世界联邦学习基准 哈尔滨工业大学；彭成实验室 ACL 2023 [PUB] [代码]
面向参数高效联邦学习的客户端定制化适配 ACL Findings 2023 [PUB]
带有适配器的多语言神经机器翻译的通信高效联邦学习 ACL Findings 2023 [PUB] [PDF] [代码]
通过蒸馏结合异构标签集进行命名实体识别的联邦领域适应 ACL Findings 2023 [PUB]
FedPETuning：当联邦学习遇上预训练语言模型的参数高效微调方法 ACL Findings 2023 [PUB]
Gboard语言模型的差分隐私联邦学习 ACL Industry Track 2023 [PUB] [PDF]
联邦学习中的后门攻击：稀有嵌入与梯度集成 首尔国立大学 EMNLP 2022 [PUB] [PDF]
印度语推文表情符号预测的联邦方法 阿尔伯塔大学 EMNLP 2022 [PUB] [PDF] [代码]
带有私有词汇表的文本分类联邦模型分解 哈尔滨工业大学；彭成实验室 EMNLP 2022 [PUB] [代码]
差分隐私文本编码器下的公平NLP模型 里尔大学 EMNLP 2022 [PUB] [PDF] [代码]
通过选择性客户间转移实现文本分类的连续联邦学习 DRIMCo GmbH；慕尼黑大学 EMNLP Findings 2022 [PUB] [PDF] [代码]
基于隐私保护的关系嵌入聚合的高效知识图谱联邦学习 kg. 利哈伊大学 EMNLP Findings 2022 [PUB] [PDF] [代码]
Dim-Krum：基于维度级Krum聚合的抗后门NLP联邦学习 北京大学 EMNLP Findings 2022 [PUB] [PDF]
跨设备联邦学习中语言模型规模的扩展 Google ACL研讨会 2022 [PUB] [PDF]
面向可扩展高效联邦学习的内在梯度压缩 牛津大学 ACL研讨会 2022 [PUB] [PDF]
ActPerFL：主动个性化联邦学习 Amazon ACL研讨会 2022 [PUB] [网页]
FedNLP：自然语言处理任务的联邦学习方法基准测试 :fire: 南加州大学 NAACL 2022 [PUB] [PDF] [代码]
带有噪声用户反馈的联邦学习 南加州大学；Amazon NAACL 2022 [PUB] [PDF]
通过联邦学习训练混合领域翻译模型 Amazon NAACL 2022 [PUB] [网页] [PDF]
多语言联邦学习的预训练模型 约翰斯·霍普金斯大学 NAACL 2022 [PUB] [PDF] [代码]
带有全局字符关联的联邦中文分词 华盛顿大学 ACL研讨会 2021 [PUB] [代码]
Efficient-FedRec：隐私保护新闻推荐的高效联邦学习框架 中国科学技术大学 EMNLP 2021 [PUB] [PDF] [代码] [视频]
通过主题记忆改进基于方面的情感分析联邦学习 香港中文大学（深圳） EMNLP 2021 [PUB] [代码] [视频]
NLP的安全高效联邦学习框架 康涅狄格大学 EMNLP 2021 [PUB] [PDF] [视频]
联邦环境下的远程监督关系抽取 中国科学院大学 EMNLP研讨会 2021 [PUB] [PDF] [代码]
带有噪声用户反馈的联邦学习 南加州大学；Amazon NAACL研讨会 2021 [PUB] [PDF]
在联邦框架下对差分隐私序列标注的探索 汉堡大学 NAACL研讨会 2021 [PUB]
理解联邦学习下语言模型中的意外记忆现象 Google NAACL研讨会 2021 [PUB] [PDF]
FedED：基于集成蒸馏的医疗关系抽取联邦学习 中国科学院 EMNLP 2020 [PUB] [视频] [解读]
面向自然语言处理的机构级联邦学习实证研究 平安科技 EMNLP研讨会 2020 [PUB]
口语理解的联邦学习 北京大学 COLING 2020 [PUB]
两阶段联邦表型分析与患者表征学习 波士顿儿童医院哈佛医学院 ACL研讨会 2019 [PUB] [PDF] [代码] [UC.]

联邦学习在顶级信息检索会议和期刊中的研究

被顶级信息检索会议和期刊收录的联邦学习论文，包括 SIGIR（年度国际ACM SIGIR信息检索研究与发展大会）。

联邦学习在顶级信息检索会议和期刊中的研究
标题 机构 会议/期刊 年份 资料
FedCIA：用于隐私保护推荐的联邦协作式信息聚合 SIGIR 2025 [论文]
NodeRec+：一种轻量级的联邦推荐系统框架 SIGIR 2025 [论文]
针对联邦在线排序学习的遗忘机制：一项可复现性研究 SIGIR 2025 [论文]
联邦推荐中的联合项目嵌入双视角探索与自适应局部-全局融合 SIGIR 2025 [论文]
ReFer：面向全用户利益的增强型垂直联邦推荐 清华大学 SIGIR 2024 [论文]
再探联邦推荐中的定向模型投毒攻击：通过多目标运输优化 浙江大学 SIGIR 2024 [论文]
FeB4RAG：在检索增强生成背景下评估联邦搜索 昆士兰大学 SIGIR 2024 [论文] [PDF] [代码]
FedUD：利用非对齐数据进行跨平台联邦点击率预测 阿里巴巴集团 SIGIR 2024 [论文]
面向异构文本的个性化联邦关系分类 国防科技大学 SIGIR 2023 [论文]
面向稀疏数据的细粒度偏好感知个性化联邦POI推荐 山东大学 SIGIR 2023 [论文]
联邦推荐系统的操纵：利用合成用户进行投毒及其应对措施 昆士兰大学 SIGIR 2023 [论文] [PDF]
FedAds：基于垂直联邦学习的隐私保护CVR预估基准 阿里巴巴集团 SIGIR 2023 [论文] [PDF] [代码]
边缘-云协同学习：结合联邦与集中式特征（短文） 浙江大学 SIGIR 2023 [论文] [PDF]
FLIRT：面向信息检索的联邦学习（扩展摘要） IMT Lucca SIGIR 2023 [论文]
在联邦在线排序学习中，非独立同分布数据是否构成威胁？ 昆士兰大学 SIGIR 2022 [论文] [代码]
FedCT：用于推荐的联邦协作式迁移学习 罗格斯大学 SIGIR 2021 [论文] [PDF] [代码]
关于联邦流水线的隐私问题 慕尼黑工业大学 SIGIR 2021 [论文]
FedCMR：联邦跨模态检索。 大连理工大学 SIGIR 2021 [论文] [代码]
用于联邦评分预测的元矩阵分解。 山东大学 SIGIR 2020 [论文] [PDF]

联邦学习在顶级数据库会议和期刊中的研究

被顶级数据库会议和期刊收录的联邦学习论文，包括 SIGMOD（ACM SIGMOD大会）、ICDE（IEEE国际数据工程大会）以及 VLDB（超大型数据库大会）。

联邦学习在顶级数据库会议和期刊中的研究
标题 机构 会议 年份 材料
PS-MI：垂直联邦学习中的准确、高效且隐私保护的数据估值 VLDB 2025 [论文] [代码]
基于缺失互补性的联邦不完全表格数据预测 VLDB 2025 [论文] [代码]
高维数据的联邦平衡聚类 VLDB 2025 [论文] [代码]
FedVSE：面向联邦数据库的隐私保护且高效的向量搜索引擎 VLDB 2025 [论文]
GORAM：用于联邦图上高效自我中心查询的图导向ORAM VLDB 2025 [论文] [代码]
联邦数据分布偏移估计 VLDB 2025 [论文] [代码]
OpenFGL：联邦图学习的全面基准 VLDB 2025 [论文] [代码]
垂直联邦学习中基于谈判的特征交易方法 ICDE 2025 [论文]
pFSSL-D：双阶段联邦半监督学习中的泛化与个性化 ICDE 2025 [论文]
FedEcover：具有高效覆盖子模型提取的快速稳定收敛的异构联邦学习 ICDE 2025 [论文]
带有隐私保护聚类的联邦轨迹相似性学习 ICDE 2025 [论文]
FedSDP：用于个性化联邦学习的联邦自衍生原型 ICDE 2025 [论文]
基于差分隐私密度估计模型的联邦数据分析。 ICDE 2025 [论文]
联邦学习中的高效数据估值近似：一种基于采样的方法。 ICDE 2025 [论文]
pFedAFM：移动边缘设备上异构联邦学习中用于数据级个性化的自适应特征混合。 ICDE 2025 [论文]
异构感知交通预测：一种隐私保护的联邦学习框架。 ICDE 2025 [论文]
使用无人机在分布式未知数据上的在线联邦学习 ICDE 2025 [论文]
追踪数据多样性：迈向垂直联邦学习中的参与者选择。 ICDE 2025 [论文]
FedMix：通过数据混合提升垂直联邦学习效果 ICDE 2024 [论文]
FedCross：通过多模型交叉聚合实现精准联邦学习 ICDE 2024 [论文]
客户帮助客户：半监督联邦学习中的交替协作 ICDE 2024 [论文]
半异步在线联邦众包 ICDE 2024 [论文]
AdaFGL：一种针对拓扑异质性的联邦节点分类新范式 ICDE 2024 [论文]
MergeSFL：带有特征合并和批量大小调节的分裂联邦学习 ICDE 2024 [论文]
LightTR：一个轻量级的联邦轨迹恢复框架 ICDE 2024 [论文]
Feed：迈向个性化有效的联邦学习 ICDE 2024 [论文]
联邦学习中的标签噪声校正：一种安全、高效且可靠的实现 ICDE 2024 [论文]
快速、鲁棒且可解释的联邦学习参与者贡献评估 ICDE 2024 [论文]
HeteFedRec：具有模型异质性的联邦推荐系统 ICDE 2024 [论文]
隐藏你的模型：一种无需参数传输的联邦推荐系统 ICDE 2024 [论文]
FedCTQ：一个基于联邦的精准高效接触追踪查询框架 ICDE 2024 [论文]
防止基于热门物品嵌入的攻击在联邦推荐中发生 ICDE 2024 [论文]
RobFL：通过特征中心分离和恶意中心检测实现的鲁棒联邦学习 ICDE 2024 [论文]
在超边缘端对LLM进行联邦微调：好的、坏的、丑陋的 TUM DEEM@SIGMOD 2024 [论文]
FedSQ：一个用于联邦向量相似度查询的安全系统 VLDB 2024 [论文]
FedSM：一个实用的联邦共享出行系统 VLDB 2024 [论文]
OFL-W3：一个基于Web 3.0的一次性联邦学习系统 VLDB 2024 [论文]
联邦学习中的贡献评估：一项全面的实验评估 VLDB 2024 [论文]
Uldp-FL：跨孤岛用户级差分隐私的联邦学习。 VLDB 2024 [论文]
基于拍卖的联邦学习性能定价 阿里集团 VLDB 2024 [论文] [代码]
用于集群式联邦学习的区块链系统，支持点对点知识转移 NJU VLDB 2024 [论文] [代码]
通信高效且可证明的联邦去学习 SDU；KAUST VLDB 2024 [论文] [PDF] [代码]
提升非独立同分布数据在异构设备上的去中心化联邦学习 USTC ICDE 2023 [论文]
异构图上联邦学习的客户端和参数动态激活 哥伦比亚大学 ICDE 2023 [论文] [代码]
FedKNOW：边缘端融合标志性任务知识的联邦持续学习 BIT ICDE 2023 [论文] [PDF]
Lumos：面向去中心化设备的异构感知联邦图学习 SJTU ICDE 2023 [论文] [PDF]
联邦物联网交互漏洞分析 MSU ICDE 2023 [论文]
非独立同分布数据上的分布规整联邦学习 BUAA ICDE 2023 [论文]
Fed-SC：高维数据上的一次性联邦子空间聚类 上海科技大学 ICDE 2023 [论文] [代码]
FLBooster：一个统一高效的联邦学习加速平台 ZJU ICDE 2023 [论文]
FedGTA：面向联邦图学习的拓扑感知平均 BIT VLDB 2023 [论文] [代码]
FS-Real：一个真实的跨设备联邦学习平台。 阿里集团 VLDB 2023 [论文] [PDF] [代码]
二分类器的联邦校准与评估。 meta VLDB 2023 [论文] [PDF] [代码]
Olive：在可信执行环境中进行的无感知联邦学习，以应对稀疏化风险。 京都大学 VLDB 2023 [论文] [PDF] [代码]
Falcon：一个隐私保护且可解释的垂直联邦学习系统。 NUS VLDB 2023 [论文] [代码]
差分隐私下的垂直联邦聚类。 普渡大学 VLDB 2023 [论文] [PDF] [代码]
FederatedScope：一个灵活的联邦学习平台，适用于异构环境。 :fire: 阿里 VLDB 2023 [论文] [PDF] [代码]
跨孤岛联邦学习的安全夏普利值。 京都大学 VLDB 2023 [论文] [PDF] [代码]
OpBoost：一个基于保序脱敏的垂直联邦树增强框架 ZJU VLDB 2022 [论文] [PDF] [代码]
Skellam混合机制：一种新颖的差分隐私联邦学习方法。 NUS VLDB 2022 [论文] [代码]
通过缓存支持的本地更新实现通信高效的垂直联邦学习训练 PKU VLDB 2022 [论文] [PDF] [代码]
FedTSC：一个用于可解释时间序列分类的安全联邦学习系统。 HIT VLDB 2022 [论文] [代码]
提高水平联邦学习中数据估值的公平性 UBC ICDE 2022 [论文] [PDF]
FedADMM：一个鲁棒的联邦深度学习框架，能够适应系统异质性 USTC ICDE 2022 [论文] [PDF] [代码]
FedMP：通过异构边缘计算中的自适应模型剪枝进行联邦学习。 USTC ICDE 2022 [论文]
非独立同分布数据孤岛上的联邦学习：一项实验研究。 :fire: NUS ICDE 2022 [论文] [PDF] [代码]
通过异构边缘计算中的智能模型迁移提升联邦学习 USTC ICDE 2022 [论文]
Samba：一个用于安全联邦多臂老虎机的系统 克莱蒙特奥弗涅大学 ICDE 2022 [论文] [代码]
FedRecAttack：针对联邦推荐的模型中毒攻击 ZJU ICDE 2022 [论文] [PDF] [代码]
通过云端未标注数据提升联邦学习 USTC ICDE 2022 [论文]
高效评估水平和垂直联邦学习的参与者贡献 USTC ICDE 2022 [论文]
联邦计算入门 沃里克大学；Facebook SIGMOD教程 2022 [论文]
BlindFL：一种不窥探你数据的垂直联邦机器学习 PKU；腾讯 SIGMOD 2022 [论文] [PDF]
一种跨孤岛联邦排序学习的有效方法 BUAA ICDE 2021 [论文] [相关论文(中文)]
垂直联邦学习中针对模型预测的特征推断攻击 NUS ICDE 2021 [论文] [PDF] [代码]
高效联邦学习模型调试 USTC ICDE 2021 [论文]
带有隐私保障的联邦矩阵分解 普渡 VLDB 2021 [论文]
投影式联邦平均与异构差分隐私。 中国人民大学 VLDB 2021 [论文] [代码]
为联邦学习启用基于SQL的数据训练调试 西蒙弗雷泽大学 VLDB 2021 [论文] [PDF] [代码]
Refiner：一个由区块链驱动的可靠激励型联邦学习系统 ZJU VLDB 2021 [论文]
Tanium Reveal：一个用于大型企业网络上查询非结构化文件数据的联邦搜索引擎 Tanium Inc. VLDB 2021 [论文] [视频]
VF2Boost：非常快速的垂直联邦梯度提升，用于跨企业学习 PKU SIGMOD 2021 [论文]
ExDRa：基于联邦原始数据的探索性数据科学 SIEMENS SIGMOD 2021 [论文]
在恶劣边缘计算环境下的区块链与联邦学习联合卸载 TJU SIGMOD研讨会 2021 [论文]
针对树模型的隐私保护垂直联邦学习 NUS VLDB 2020 [论文] [PDF] [视频] [代码]

fl 在顶级网络会议和期刊中

联邦学习论文被顶级数据库会议和期刊录用，包括 SIGCOMM（计算机通信应用、技术、架构与协议大会）、INFOCOM（IEEE计算机通信大会）、MobiCom（ACM/IEEE移动计算与网络国际会议）、NSDI（网络系统设计与实现研讨会）以及 WWW（万维网大会）。

fl 在顶级网络会议和期刊中
标题 所属机构 会议/期刊 年份 文献
一种面向能耗感知的联邦学习轻量级仿真框架 SIGCOMM（海报与演示） 2025 [PUB]
NEBULA——面向异构网络的去中心化联邦学习 SIGCOMM（海报与演示） 2025 [PUB]
联邦推理：迈向边缘设备上的协作式隐私保护推理 SIGCOMM（海报与演示） 2025 [PUB]
针对图数据上垂直联邦学习的偏好画像攻击 INFOCOM 2025 [PUB]
FedGPA：用于边缘异常检测的全局-个性化协同联邦学习 INFOCOM 2025 [PUB]
基于异构量化和LoRA的大语言模型联邦自适应微调 INFOCOM 2025 [PUB]
FLM-TopK：通过稀疏化区间梯度加速联邦大语言模型调优 INFOCOM 2025 [PUB]
面向通信高效分布式极小极大优化的客户端采样 INFOCOM 2025 [PUB]
面向不可靠网络系统的鲁棒上下文组合多臂老虎机问题 INFOCOM 2025 [PUB]
ElasticFed：面向边缘联邦持续学习的大小模型协同训练 INFOCOM 2025 [PUB]
γ-FedHT：联邦学习中的步长感知硬阈值梯度压缩 INFOCOM 2025 [PUB]
PSFL：具有收敛性保证的并行-串行联邦学习 INFOCOM 2025 [PUB]
GraphRx：面向上行神经接收机的多小区基于图的协作学习 INFOCOM 2025 [PUB]
输入完整性和结果真实性：迈向联邦学习中的可信聚合 INFOCOM 2025 [PUB]
具有差分隐私和容错能力的轻量级联邦学习 INFOCOM 2025 [PUB]
通信高效的异步随机梯度下降 INFOCOM 2025 [PUB]
GeoFL：高效地理分布跨设备联邦学习框架 INFOCOM 2025 [PUB]
FedPDA：用于降低神经接收机在线适应频率的协作学习 INFOCOM 2025 [PUB]
LCO-AGQ：面向联邦学习的轻量级客户端导向自适应梯度量化算法 INFOCOM 2025 [PUB]
FedEXT：具有边缘模型互补扩展的差异化联邦学习 INFOCOM 2025 [PUB]
FedFetch：通过自适应下游预取加速联邦学习 INFOCOM 2025 [PUB]
基于相似性引导的异构边缘计算上联邦智能快速部署 INFOCOM 2025 [PUB]
CARE：面向预算有限请求方的兼容性感知联邦学习激励机制 INFOCOM 2025 [PUB]
面向延迟信息的无线在线联邦学习的受限空中模型更新 INFOCOM 2025 [PUB]
面向数据中心协作式网络优化的多任务强化学习 INFOCOM 2025 [PUB]
走向联邦推理：面向协作式边缘AI的在线模型集成框架 INFOCOM 2025 [PUB]
VaniKG：针对鲁棒联邦聚合的消失关键梯度攻击与防御 INFOCOM 2025 [PUB]
利用量子密钥分发对抗跨silos联邦学习中的梯度深度泄漏 INFOCOM 2025 [PUB]
FedUFD：利用联邦不确定性驱动的特征蒸馏实现个性化边缘计算 INFOCOM 2025 [PUB]
利用可迁移图神经网络加速动态D2D网络中的聚类联邦学习 INFOCOM 2025 [PUB]
面向流式数据的AoI感知联邦遗忘：结合在线客户端选择与定价 INFOCOM 2025 [PUB]
动态图遗忘：一种通用且高效的梯度变换后处理方法 WWW 2025 [PUB]
利用潜在环境赋能联邦图理性学习 WWW 2025 [PUB]
Aegis：面向联邦推荐系统、抵御属性推断攻击的训练后属性遗忘 WWW 2025 [PUB]
P4GCN：具有隐私保护的双端图卷积网络的垂直联邦社交推荐 WWW 2025 [PUB]
具有时序相关性的无限数据流局部差分隐私发布 WWW 2025 [PUB]
在隐私风险下，遗忘激励学习 WWW 2025 [PUB]
Maverick：基于对比学习的个性化边缘辅助联邦学习 WWW 2025 [PUB]
水平联邦异构图学习：应对数据分布挑战的多尺度自适应方案 WWW 2025 [PUB]
处理联邦学习中的噪声数据：一种灵活定价的激励机制 WWW 2025 [PUB]
大型（视觉）语言模型中基于自我比较的数据集成员身份推断 WWW 2025 [PUB]
基于解耦表征学习的联邦图异常检测 WWW 2025 [PUB]
FedMobile：支持不完全模态的知识贡献感知多模态联邦学习 WWW 2025 [PUB]
子图联邦遗忘 WWW 2025 [PUB]
基于自适应知识融合的冷启动用户个性化联邦推荐 WWW 2025 [PUB]
NI-GDBA：基于联邦图学习中自适应扰动的非侵入式分布式后门攻击 WWW 2025 [PUB]
FedRIR：重新思考联邦学习中的信息表示 WWW 2025 [PUB]
PM-MOE：面向个性化联邦学习的私有模型参数专家混合 WWW 2025 [PUB]
可证明鲁棒的联邦强化学习 WWW 2025 [PUB]
MoCFL：面向高度动态网络的移动集群联邦学习框架 WWW 2025 [PUB]
Flock：基于实用区块链状态通道的鲁棒且隐私保护的联邦学习 WWW 2025 [PUB]
PAPAYA联邦分析栈：兼顾隐私、可扩展性和实用性 NSDI 2025 [PUB] [SLIDE]
破解安全聚合：联邦学习中聚合梯度导致的标签泄露 INFOCOM 2024 [PUB]
联邦遗忘中的策略性数据撤销 INFOCOM 2024 [PUB]
FedTC：通过变换编码实现通信高效的联邦学习 INFOCOM 2024 [PUB]
在提供模型即服务的同时进行联邦学习：联合训练与推理优化 INFOCOM 2024 [PUB]
FairFed：通过合作式Shapley值提升联邦学习中贡献评估的公平性和效率 INFOCOM 2024 [PUB]
DPBalance：面向模型即服务的联邦学习的高效公平隐私预算调度 INFOCOM 2024 [[PUB](https:

版本历史

v1.0-alpha2024/12/30
v0.9.9-alpha2024/09/30
v0.9.8-alpha2023/12/31
v0.9.6-alpha2023/06/06
v0.9.0-alpha2022/09/22
v0.8.0-alpha2022/09/16

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