Optimal Client Sampling for Federated Learning

26 October 2020

Papers citing "Optimal Client Sampling for Federated Learning"

32 / 32 papers shown

Title
FedFetch: Faster Federated Learning with Adaptive Downstream Prefetching Qifan Yan Andrew Liu Shiqi He Mathias Lécuyer Ivan Beschastnikh FedML 36 0 0 21 Apr 2025
Communication-Efficient and Personalized Federated Foundation Model Fine-Tuning via Tri-Matrix Adaptation Y. Li Bo Liu Sheng Huang Z. Zhang Xiaotong Yuan Richang Hong 46 0 0 31 Mar 2025
Biased Federated Learning under Wireless Heterogeneity Muhammad Faraz Ul Abrar Nicolò Michelusi FedML 44 0 0 08 Mar 2025
Scalable Decentralized Learning with Teleportation Yuki Takezawa Sebastian U. Stich 56 1 0 25 Jan 2025
Attribute Inference Attacks for Federated Regression Tasks Francesco Diana Othmane Marfoq Chuan Xu Giovanni Neglia F. Giroire Eoin Thomas AAML 163 1 0 19 Nov 2024
Understanding Server-Assisted Federated Learning in the Presence of Incomplete Client Participation Haibo Yang Pei-Yuan Qiu Prashant Khanduri Minghong Fang Jia Liu FedML 40 1 0 04 May 2024
Efficient Unbiased Sparsification Leighton Barnes Timothy Chow Emma Cohen Keith Frankston Benjamin Howard Fred Kochman Daniel Scheinerman Jeffrey VanderKam OT 24 1 0 22 Feb 2024
A Framework for Incentivized Collaborative Learning Xinran Wang Qi Le Ahmad Faraz Khan Jie Ding A. Anwar FedML 37 4 0 26 May 2023
Federated Gradient Matching Pursuit Halyun Jeong Deanna Needell Jing Qin FedML 35 1 0 20 Feb 2023
Distributed Stochastic Optimization under a General Variance Condition Kun-Yen Huang Xiao Li Shin-Yi Pu FedML 37 5 0 30 Jan 2023
Entropy-driven Fair and Effective Federated Learning Lung-Chuang Wang Zhichao Wang Sai Praneeth Karimireddy Xiaoying Tang Xiaoying Tang FedML 33 9 0 29 Jan 2023
Uplink Scheduling in Federated Learning: an Importance-Aware Approach via Graph Representation Learning Marco Skocaj Pedro Enrique Iturria-Rivera Roberto Verdone Melike Erol-Kantarci 30 1 0 27 Jan 2023
When Do Curricula Work in Federated Learning? Saeed Vahidian Sreevatsank Kadaveru Woo-Ram Baek Weijia Wang Vyacheslav Kungurtsev C. L. P. Chen M. Shah Bill Lin FedML 32 11 0 24 Dec 2022
GlueFL: Reconciling Client Sampling and Model Masking for Bandwidth Efficient Federated Learning Shiqi He Qifan Yan Feijie Wu Lanjun Wang Mathias Lécuyer Ivan Beschastnikh FedML 36 7 0 03 Dec 2022
Client Selection in Federated Learning: Principles, Challenges, and Opportunities Lei Fu Huan Zhang Ge Gao Mi Zhang Xin Liu FedML 32 115 0 03 Nov 2022
Communication-Efficient Local SGD with Age-Based Worker Selection Feng Zhu Jingjing Zhang Xin Eric Wang 18 1 0 31 Oct 2022
Local Model Reconstruction Attacks in Federated Learning and their Uses Ilias Driouich Chuan Xu Giovanni Neglia F. Giroire Eoin Thomas AAML FedML 29 2 0 28 Oct 2022
Fast Heterogeneous Federated Learning with Hybrid Client Selection Guangyuan Shen D. Gao Duanxiao Song Libin Yang Xukai Zhou Shirui Pan W. Lou Fang Zhou FedML 27 12 0 10 Aug 2022
DELTA: Diverse Client Sampling for Fasting Federated Learning Lung-Chuang Wang Yongxin Guo Tao R. Lin Xiaoying Tang FedML 23 21 0 27 May 2022
FedAvg with Fine Tuning: Local Updates Lead to Representation Learning Liam Collins Hamed Hassani Aryan Mokhtari Sanjay Shakkottai FedML 24 75 0 27 May 2022
Fine-tuning Global Model via Data-Free Knowledge Distillation for Non-IID Federated Learning Lin Zhang Li Shen Liang Ding Dacheng Tao Ling-Yu Duan FedML 28 252 0 17 Mar 2022
Learnings from Federated Learning in the Real world Christophe Dupuy Tanya Roosta Leo Long Clement Chung Rahul Gupta A. Avestimehr FedML 20 10 0 08 Feb 2022
Variance-Reduced Heterogeneous Federated Learning via Stratified Client Selection Guangyuan Shen D. Gao Libin Yang Fang Zhou Duanxiao Song Wei Lou Shirui Pan FedML 12 8 0 15 Jan 2022
Adaptive Client Sampling in Federated Learning via Online Learning with Bandit Feedback Boxin Zhao Lingxiao Wang Mladen Kolar Ziqi Liu Zhiqiang Zhang Jun Zhou Chaochao Chen FedML 26 10 0 28 Dec 2021
Sparsified Secure Aggregation for Privacy-Preserving Federated Learning Irem Ergun Hasin Us Sami Başak Güler FedML 28 25 0 23 Dec 2021
Papaya: Practical, Private, and Scalable Federated Learning Dzmitry Huba John Nguyen Kshitiz Malik Ruiyu Zhu Michael G. Rabbat ... H. Srinivas Kaikai Wang Anthony Shoumikhin Jesik Min Mani Malek FedML 107 137 0 08 Nov 2021
Resource-Efficient Federated Learning A. Abdelmoniem Atal Narayan Sahu Marco Canini Suhaib A. Fahmy FedML 25 52 0 01 Nov 2021
A Field Guide to Federated Optimization Jianyu Wang Zachary B. Charles Zheng Xu Gauri Joshi H. B. McMahan ... Mi Zhang Tong Zhang Chunxiang Zheng Chen Zhu Wennan Zhu FedML 178 411 0 14 Jul 2021
On Large-Cohort Training for Federated Learning Zachary B. Charles Zachary Garrett Zhouyuan Huo Sergei Shmulyian Virginia Smith FedML 19 112 0 15 Jun 2021
FedNL: Making Newton-Type Methods Applicable to Federated Learning M. Safaryan Rustem Islamov Xun Qian Peter Richtárik FedML 20 77 0 05 Jun 2021
Local Adaptivity in Federated Learning: Convergence and Consistency Jianyu Wang Zheng Xu Zachary Garrett Zachary B. Charles Luyang Liu Gauri Joshi FedML 24 38 0 04 Jun 2021
Linear Convergence of Gradient and Proximal-Gradient Methods Under the Polyak-Łojasiewicz Condition Hamed Karimi J. Nutini Mark W. Schmidt 133 1,198 0 16 Aug 2016