"federated learning" Papers

Federated Neuro-Symbolic Learning

Pengwei Xing, Songtao Lu, Han Yu

Federated Optimization with Doubly Regularized Drift Correction

Xiaowen Jiang, Anton Rodomanov, Sebastian Stich

Federated Self-Explaining GNNs with Anti-shortcut Augmentations

Linan Yue, Qi Liu, Weibo Gao et al.

FedFixer: Mitigating Heterogeneous Label Noise in Federated Learning

Xinyuan Ji, Zhaowei Zhu, Wei Xi et al.

FedLMT: Tackling System Heterogeneity of Federated Learning via Low-Rank Model Training with Theoretical Guarantees

Jiahao Liu, Yipeng Zhou, Di Wu et al.

FedLPS: Heterogeneous Federated Learning for Multiple Tasks with Local Parameter Sharing

Yongzhe Jia, Xuyun Zhang, Amin Beheshti et al.

FedNS: A Fast Sketching Newton-Type Algorithm for Federated Learning

Fed-QSSL: A Framework for Personalized Federated Learning under Bitwidth and Data Heterogeneity

Yiyue Chen, Haris Vikalo, Chianing Wang

FedRC: Tackling Diverse Distribution Shifts Challenge in Federated Learning by Robust Clustering

Yongxin Guo, Xiaoying Tang, Tao Lin

FedREDefense: Defending against Model Poisoning Attacks for Federated Learning using Model Update Reconstruction Error

Yueqi Xie, Minghong Fang, Neil Gong

FedSC: Provable Federated Self-supervised Learning with Spectral Contrastive Objective over Non-i.i.d. Data

Shusen Jing, Anlan Yu, Shuai Zhang et al.

Formal Logic Enabled Personalized Federated Learning through Property Inference

Ziyan An, Taylor Johnson, Meiyi Ma

Improved Modelling of Federated Datasets using Mixtures-of-Dirichlet-Multinomials

Jonathan Scott, Aine E Cahill

Lessons from Generalization Error Analysis of Federated Learning: You May Communicate Less Often!

Milad Sefidgaran, Romain Chor, Abdellatif Zaidi et al.

Locally Estimated Global Perturbations are Better than Local Perturbations for Federated Sharpness-aware Minimization

Ziqing Fan, Shengchao Hu, Jiangchao Yao et al.

MH-pFLID: Model Heterogeneous personalized Federated Learning via Injection and Distillation for Medical Data Analysis

Luyuan Xie, Manqing Lin, Tianyu Luan et al.

Multi-Dimensional Fair Federated Learning

Cong Su, Guoxian Yu, Jun Wang et al.

Noise-Aware Algorithm for Heterogeneous Differentially Private Federated Learning

Saber Malekmohammadi, Yaoliang Yu, YANG CAO

No Prejudice! Fair Federated Graph Neural Networks for Personalized Recommendation

Nimesh Agrawal, Anuj Sirohi, Sandeep Kumar et al.

On the Role of Server Momentum in Federated Learning

Jianhui Sun, Xidong Wu, Heng Huang et al.

Overcoming Data and Model heterogeneities in Decentralized Federated Learning via Synthetic Anchors

Chun-Yin Huang, Kartik Srinivas, Xin Zhang et al.

Performative Federated Learning: A Solution to Model-Dependent and Heterogeneous Distribution Shifts

Kun Jin, Tongxin Yin, Zhongzhu Chen et al.

Point Transformer with Federated Learning for Predicting Breast Cancer HER2 Status from Hematoxylin and Eosin-Stained Whole Slide Images

Bao Li, Zhenyu Liu, Lizhi Shao et al.

PPIDSG: A Privacy-Preserving Image Distribution Sharing Scheme with GAN in Federated Learning

Yuting Ma, Yuanzhi Yao, Xiaohua Xu

PrE-Text: Training Language Models on Private Federated Data in the Age of LLMs

Charlie Hou, Akshat Shrivastava, Hongyuan Zhan et al.

Private and Federated Stochastic Convex Optimization: Efficient Strategies for Centralized Systems

Roie Reshef, Kfir Levy

Private Heterogeneous Federated Learning Without a Trusted Server Revisited: Error-Optimal and Communication-Efficient Algorithms for Convex Losses

Changyu Gao, Andrew Lowy, Xingyu Zhou et al.

Provable Benefits of Local Steps in Heterogeneous Federated Learning for Neural Networks: A Feature Learning Perspective

Yajie Bao, Michael Crawshaw, Mingrui Liu

Pursuing Overall Welfare in Federated Learning through Sequential Decision Making

Seok-Ju Hahn, Gi-Soo Kim, Junghye Lee

Ranking-based Client Imitation Selection for Efficient Federated Learning

Chunlin Tian, Zhan Shi, Xinpeng Qin et al.

Recurrent Early Exits for Federated Learning with Heterogeneous Clients

Royson Lee, Javier Fernandez-Marques, Xu Hu et al.

Resisting Backdoor Attacks in Federated Learning via Bidirectional Elections and Individual Perspective

Zhen Qin, Feiyi Chen, Chen Zhi et al.

Rethinking the Flat Minima Searching in Federated Learning

Taehwan Lee, Sung Whan Yoon

Self-Driven Entropy Aggregation for Byzantine-Robust Heterogeneous Federated Learning

Wenke Huang, Zekun Shi, Mang Ye et al.

SILVER: Single-loop variance reduction and application to federated learning

Kazusato Oko, Shunta Akiyama, Denny Wu et al.

Understanding Server-Assisted Federated Learning in the Presence of Incomplete Client Participation

Haibo Yang, Peiwen Qiu, Prashant Khanduri et al.

Watch Your Head: Assembling Projection Heads to Save the Reliability of Federated Models

Authors: Jinqian Chen, Jihua Zhu, Qinghai Zheng et al.