DELTA: Diverse Client Sampling for Fasting Federated Learning

27 May 2022

Papers citing "DELTA: Diverse Client Sampling for Fasting Federated Learning"

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Title
Towards Optimal Heterogeneous Client Sampling in Multi-Model Federated Learning Haoran Zhang Zejun Gong Zekai Li Marie Siew Carlee Joe-Wong Rachid El-Azouzi 98 0 0 07 Apr 2025
A Unified Analysis of Federated Learning with Arbitrary Client Participation Shiqiang Wang Mingyue Ji FedML 76 56 0 31 Dec 2024
On the effectiveness of partial variance reduction in federated learning with heterogeneous data Yue Liu Mikkel N. Schmidt T. S. Alstrøm Sebastian U. Stich FedML 61 9 0 05 Dec 2022
FLIS: Clustered Federated Learning via Inference Similarity for Non-IID Data Distribution Mahdi Morafah Saeed Vahidian Weijia Wang Bill Lin OOD FedML 23 37 0 20 Aug 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 57 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 66 61 0 28 Jul 2022
A Computation and Communication Efficient Method for Distributed Nonconvex Problems in the Partial Participation Setting Alexander Tyurin Peter Richtárik FedML 22 4 0 31 May 2022
Communication-Efficient Device Scheduling for Federated Learning Using Stochastic Optimization Jake B. Perazzone Shiqiang Wang Mingyue Ji Kevin S. Chan FedML 43 74 0 19 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 100 11 0 28 Dec 2021
Towards Federated Learning on Time-Evolving Heterogeneous Data Yongxin Guo Tao R. Lin Xiaoying Tang FedML 40 30 0 25 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 67 172 0 21 Dec 2021
FedSoft: Soft Clustered Federated Learning with Proximal Local Updating Yichen Ruan Carlee Joe-Wong FedML 43 90 0 11 Dec 2021
Context-Aware Online Client Selection for Hierarchical Federated Learning Zhe Qu Rui Duan Lixing Chen Jie Xu Zhuo Lu Yao-Hong Liu 61 61 0 02 Dec 2021
A General Theory for Client Sampling in Federated Learning Yann Fraboni Richard Vidal Laetitia Kameni Marco Lorenzi FedML 24 13 0 26 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 252 415 0 14 Jul 2021
Federated Graph Classification over Non-IID Graphs Han Xie Jing Ma Li Xiong Carl Yang FedML 64 158 0 25 Jun 2021
Clustered Sampling: Low-Variance and Improved Representativity for Clients Selection in Federated Learning Yann Fraboni Richard Vidal Laetitia Kameni Marco Lorenzi FedML 46 189 0 12 May 2021
Advances in Importance Sampling Victor Elvira Luca Martino AI4TS 73 106 0 10 Feb 2021
Federated Multi-Armed Bandits Chengshuai Shi Cong Shen FedML 96 93 0 28 Jan 2021
Achieving Linear Speedup with Partial Worker Participation in Non-IID Federated Learning Haibo Yang Minghong Fang Jia Liu FedML 50 256 0 27 Jan 2021
Bandit-based Communication-Efficient Client Selection Strategies for Federated Learning Yae Jee Cho Samarth Gupta Gauri Joshi Osman Yağan FedML 45 68 0 14 Dec 2020
Federated Learning under Importance Sampling Elsa Rizk Stefan Vlaski Ali H. Sayed FedML 45 53 0 14 Dec 2020
Dynamic Clustering in Federated Learning Yeongwoo Kim Ezeddin Al Hakim Johan Haraldson Henrik Eriksson J. M. B. D. Silva Carlo Fischione 38 57 0 07 Dec 2020
Stochastic Client Selection for Federated Learning with Volatile Clients Tiansheng Huang Weiwei Lin Li Shen Keqin Li Albert Y. Zomaya FedML 80 98 0 17 Nov 2020
Budgeted Online Selection of Candidate IoT Clients to Participate in Federated Learning Ihab Mohammed Shadha Tabatabai Ala I. Al-Fuqaha Faissal El Bouanani Junaid Qadir Basheer Qolomany Mohsen Guizani 45 60 0 16 Nov 2020
Optimal Client Sampling for Federated Learning Jiajun He Samuel Horváth Peter Richtárik FedML 65 195 0 26 Oct 2020
HeteroFL: Computation and Communication Efficient Federated Learning for Heterogeneous Clients Enmao Diao Jie Ding Vahid Tarokh FedML 91 550 0 03 Oct 2020
Client Selection in Federated Learning: Convergence Analysis and Power-of-Choice Selection Strategies Yae Jee Cho Jianyu Wang Gauri Joshi FedML 131 404 0 03 Oct 2020
Mime: Mimicking Centralized Stochastic Algorithms in Federated Learning Sai Praneeth Karimireddy Martin Jaggi Satyen Kale M. Mohri Sashank J. Reddi Sebastian U. Stich A. Suresh FedML 73 217 0 08 Aug 2020
Communication-Efficient Federated Learning via Optimal Client Sampling Mónica Ribero H. Vikalo FedML 50 94 0 30 Jul 2020
Tackling the Objective Inconsistency Problem in Heterogeneous Federated Optimization Jianyu Wang Qinghua Liu Hao Liang Gauri Joshi H. Vincent Poor MoMe FedML 45 1,321 0 15 Jul 2020
Multi-Armed Bandit Based Client Scheduling for Federated Learning Wenchao Xia Tony Q.S. Quek Kun Guo Wanli Wen Howard H. Yang Hongbo Zhu FedML 83 219 0 05 Jul 2020
Personalized Federated Learning with Moreau Envelopes Canh T. Dinh N. H. Tran Tuan Dung Nguyen FedML 65 982 0 16 Jun 2020
Ensemble Distillation for Robust Model Fusion in Federated Learning Tao R. Lin Lingjing Kong Sebastian U. Stich Martin Jaggi FedML 74 1,031 0 12 Jun 2020
FedPD: A Federated Learning Framework with Optimal Rates and Adaptivity to Non-IID Data Xinwei Zhang Mingyi Hong S. Dhople W. Yin Yang Liu FedML 44 229 0 22 May 2020
A Unified Theory of Decentralized SGD with Changing Topology and Local Updates Anastasia Koloskova Nicolas Loizou Sadra Boreiri Martin Jaggi Sebastian U. Stich FedML 76 499 0 23 Mar 2020
Adaptive Federated Optimization Sashank J. Reddi Zachary B. Charles Manzil Zaheer Zachary Garrett Keith Rush Jakub Konecný Sanjiv Kumar H. B. McMahan FedML 88 1,417 0 29 Feb 2020
Better Theory for SGD in the Nonconvex World Ahmed Khaled Peter Richtárik 45 182 0 09 Feb 2020
Accelerating Federated Learning via Momentum Gradient Descent Wei Liu Li Chen Yunfei Chen Wenyi Zhang FedML AI4CE 60 292 0 08 Oct 2019
Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification T. Hsu Qi Matthew Brown FedML 113 1,128 0 13 Sep 2019
On the Convergence of FedAvg on Non-IID Data Xiang Li Kaixuan Huang Wenhao Yang Shusen Wang Zhihua Zhang FedML 125 2,311 0 04 Jul 2019
Federated Optimization in Heterogeneous Networks Tian Li Anit Kumar Sahu Manzil Zaheer Maziar Sanjabi Ameet Talwalkar Virginia Smith FedML 87 5,105 0 14 Dec 2018
LEAF: A Benchmark for Federated Settings S. Caldas Sai Meher Karthik Duddu Peter Wu Tian Li Jakub Konecný H. B. McMahan Virginia Smith Ameet Talwalkar FedML 113 1,410 0 03 Dec 2018
Parallel Restarted SGD with Faster Convergence and Less Communication: Demystifying Why Model Averaging Works for Deep Learning Hao Yu Sen Yang Shenghuo Zhu MoMe FedML 66 602 0 17 Jul 2018
Not All Samples Are Created Equal: Deep Learning with Importance Sampling Angelos Katharopoulos François Fleuret 62 515 0 02 Mar 2018
Safe Adaptive Importance Sampling Sebastian U. Stich Anant Raj Martin Jaggi 54 54 0 07 Nov 2017
Biased Importance Sampling for Deep Neural Network Training Angelos Katharopoulos François Fleuret 42 67 0 31 May 2017
Communication-Efficient Learning of Deep Networks from Decentralized Data H. B. McMahan Eider Moore Daniel Ramage S. Hampson Blaise Agüera y Arcas FedML 246 17,328 0 17 Feb 2016
Variance Reduction in SGD by Distributed Importance Sampling Guillaume Alain Alex Lamb Chinnadhurai Sankar Aaron Courville Yoshua Bengio FedML 62 198 0 20 Nov 2015
Stochastic Optimization with Importance Sampling P. Zhao Tong Zhang 72 343 0 13 Jan 2014