Optimal Client Sampling for Federated Learning

26 October 2020

Papers citing "Optimal Client Sampling for Federated Learning"

50 / 102 papers shown

Title
Federated Learning with Regularized Client Participation Grigory Malinovsky Samuel Horváth Konstantin Burlachenko Peter Richtárik FedML 31 13 0 07 Feb 2023
Distributed Stochastic Optimization under a General Variance Condition Kun-Yen Huang Xiao Li Shin-Yi Pu FedML 40 6 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 38 1 0 27 Jan 2023
When to Trust Aggregated Gradients: Addressing Negative Client Sampling in Federated Learning Wenkai Yang Yankai Lin Guangxiang Zhao Peng Li Jie Zhou Xu Sun FedML 16 2 0 25 Jan 2023
Federated Learning under Heterogeneous and Correlated Client Availability Angelo Rodio Francescomaria Faticanti Othmane Marfoq Giovanni Neglia Emilio Leonardi FedML 13 27 0 11 Jan 2023
Network Adaptive Federated Learning: Congestion and Lossy Compression Parikshit Hegde G. Veciana Aryan Mokhtari FedML 18 4 0 11 Jan 2023
Can 5th Generation Local Training Methods Support Client Sampling? Yes! Michal Grudzieñ Grigory Malinovsky Peter Richtárik 24 29 0 29 Dec 2022
When Do Curricula Work in Federated Learning? Saeed Vahidian Sreevatsank Kadaveru Woo-Ram Baek Weijia Wang Vyacheslav Kungurtsev Cheng Chen M. Shah Bill Lin FedML 40 11 0 24 Dec 2022
Deep Unfolding-based Weighted Averaging for Federated Learning in Heterogeneous Environments Ayano Nakai-Kasai T. Wadayama FedML 27 0 0 23 Dec 2022
Adaptive Control of Client Selection and Gradient Compression for Efficient Federated Learning Zhida Jiang Yang Xu Hong-Ze Xu Zhiyuan Wang Chen Qian 20 9 0 19 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 42 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 37 115 0 03 Nov 2022
Communication-Efficient Local SGD with Age-Based Worker Selection Feng Zhu Jingjing Zhang Xin Wang 32 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 32 2 0 28 Oct 2022
A Snapshot of the Frontiers of Client Selection in Federated Learning Gergely Németh M. Lozano Novi Quadrianto Nuria Oliver FedML 102 14 0 27 Sep 2022
Faster federated optimization under second-order similarity Ahmed Khaled Chi Jin FedML 56 17 0 06 Sep 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 39 12 0 10 Aug 2022
FedVARP: Tackling the Variance Due to Partial Client Participation in Federated Learning Divyansh Jhunjhunwala Pranay Sharma Aushim Nagarkatti Gauri Joshi FedML 49 42 0 28 Jul 2022
Study of the performance and scalability of federated learning for medical imaging with intermittent clients Judith Sáinz-Pardo Díaz Á. García FedML OOD 24 51 0 18 Jul 2022
Variance Reduced ProxSkip: Algorithm, Theory and Application to Federated Learning Grigory Malinovsky Kai Yi Peter Richtárik FedML 42 38 0 09 Jul 2022
DELTA: Diverse Client Sampling for Fasting Federated Learning Lung-Chuang Wang Yongxin Guo Tao R. Lin Xiaoying Tang FedML 23 22 0 27 May 2022
FedAvg with Fine Tuning: Local Updates Lead to Representation Learning Liam Collins Hamed Hassani Aryan Mokhtari Sanjay Shakkottai FedML 32 75 0 27 May 2022
Combating Client Dropout in Federated Learning via Friend Model Substitution Heqiang Wang Jie Xu FedML 25 5 0 26 May 2022
Privacy Amplification via Random Participation in Federated Learning Burak Hasircioglu Deniz Gunduz FedML 19 1 0 03 May 2022
FedShuffle: Recipes for Better Use of Local Work in Federated Learning Samuel Horváth Maziar Sanjabi Lin Xiao Peter Richtárik Michael G. Rabbat FedML 33 21 0 27 Apr 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 28 253 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 22 10 0 08 Feb 2022
Server-Side Stepsizes and Sampling Without Replacement Provably Help in Federated Optimization Grigory Malinovsky Konstantin Mishchenko Peter Richtárik FedML 17 24 0 26 Jan 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 19 8 0 15 Jan 2022
Multi-Model Federated Learning Neelkamal Bhuyan Sharayu Moharir FedML 11 19 0 07 Jan 2022
Adaptive Client Sampling in Federated Learning via Online Learning with Bandit Feedback Boxin Zhao Lingxiao Wang Mladen Kolar Ziqi Liu Qing Cui Jun Zhou Chaochao Chen FedML 34 10 0 28 Dec 2021
Sparsified Secure Aggregation for Privacy-Preserving Federated Learning Irem Ergun Hasin Us Sami Başak Güler FedML 36 26 0 23 Dec 2021
Tackling System and Statistical Heterogeneity for Federated Learning with Adaptive Client Sampling Bing Luo Wenli Xiao Shiqiang Wang Jianwei Huang Leandros Tassiulas FedML 42 168 0 21 Dec 2021
The Internet of Federated Things (IoFT): A Vision for the Future and In-depth Survey of Data-driven Approaches for Federated Learning Raed Al Kontar Naichen Shi Xubo Yue Seokhyun Chung E. Byon ... C. Okwudire Garvesh Raskutti R. Saigal Karandeep Singh Ye Zhisheng FedML 38 50 0 09 Nov 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 113 137 0 08 Nov 2021
Resource-Efficient Federated Learning A. Abdelmoniem Atal Narayan Sahu Marco Canini Suhaib A. Fahmy FedML 32 52 0 01 Nov 2021
A General Theory for Client Sampling in Federated Learning Yann Fraboni Richard Vidal Laetitia Kameni Marco Lorenzi FedML 6 13 0 26 Jul 2021
Accelerating Federated Edge Learning via Optimized Probabilistic Device Scheduling Maojun Zhang Guangxu Zhu Shuai Wang Jiamo Jiang C. Zhong Shuguang Cui FedML 16 5 0 24 Jul 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 187 412 0 14 Jul 2021
On Large-Cohort Training for Federated Learning Zachary B. Charles Zachary Garrett Zhouyuan Huo Sergei Shmulyian Virginia Smith FedML 21 113 0 15 Jun 2021
Securing Secure Aggregation: Mitigating Multi-Round Privacy Leakage in Federated Learning Jinhyun So Ramy E. Ali Başak Güler Jiantao Jiao Salman Avestimehr FedML 37 77 0 07 Jun 2021
FedNL: Making Newton-Type Methods Applicable to Federated Learning M. Safaryan Rustem Islamov Xun Qian Peter Richtárik FedML 33 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 29 39 0 04 Jun 2021
Node Selection Toward Faster Convergence for Federated Learning on Non-IID Data Hongda Wu Ping Wang FedML 26 135 0 14 May 2021
Clustered Sampling: Low-Variance and Improved Representativity for Clients Selection in Federated Learning Yann Fraboni Richard Vidal Laetitia Kameni Marco Lorenzi FedML 13 184 0 12 May 2021
Sustainable Federated Learning Başak Güler Aylin Yener 14 13 0 22 Feb 2021
Energy-Harvesting Distributed Machine Learning Başak Güler Aylin Yener FedML 23 15 0 10 Feb 2021
FedProf: Selective Federated Learning with Representation Profiling Wentai Wu Ligang He Weiwei Lin Carsten Maple FedML 30 1 0 02 Feb 2021
Stochastic Client Selection for Federated Learning with Volatile Clients Tiansheng Huang Weiwei Lin Li Shen Keqin Li Albert Y. Zomaya FedML 14 97 0 17 Nov 2020