Federated Learning under Importance Sampling

14 December 2020

Papers citing "Federated Learning under Importance Sampling"

35 / 35 papers shown

Title
Fast-Convergent Federated Learning Hung T. Nguyen Vikash Sehwag Seyyedali Hosseinalipour Christopher G. Brinton M. Chiang H. Vincent Poor FedML 46 192 0 26 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 70 219 0 05 Jul 2020
Dynamic Federated Learning Elsa Rizk Stefan Vlaski Ali H. Sayed FedML 75 25 0 20 Feb 2020
A Joint Learning and Communications Framework for Federated Learning over Wireless Networks Mingzhe Chen Zhaohui Yang Walid Saad Changchuan Yin H. Vincent Poor Shuguang Cui FedML 59 1,181 0 17 Sep 2019
First Analysis of Local GD on Heterogeneous Data Ahmed Khaled Konstantin Mishchenko Peter Richtárik FedML 32 172 0 10 Sep 2019
Energy-Efficient Radio Resource Allocation for Federated Edge Learning Qunsong Zeng Yuqing Du K. Leung Kaibin Huang 32 226 0 13 Jul 2019
On the Convergence of FedAvg on Non-IID Data Xiang Li Kaixuan Huang Wenhao Yang Shusen Wang Zhihua Zhang FedML 123 2,311 0 04 Jul 2019
Variational Federated Multi-Task Learning Luca Corinzia Ami Beuret J. M. Buhmann FedML 41 161 0 14 Jun 2019
Adaptive Gradient-Based Meta-Learning Methods M. Khodak Maria-Florina Balcan Ameet Talwalkar FedML 54 355 0 06 Jun 2019
Fair Resource Allocation in Federated Learning Tian Li Maziar Sanjabi Ahmad Beirami Virginia Smith FedML 110 793 0 25 May 2019
Hybrid-FL for Wireless Networks: Cooperative Learning Mechanism Using Non-IID Data Naoya Yoshida Takayuki Nishio M. Morikura Koji Yamamoto Ryo Yonetani 58 137 0 17 May 2019
Client-Edge-Cloud Hierarchical Federated Learning Lumin Liu Jun Zhang S. H. Song Khaled B. Letaief FedML 53 736 0 16 May 2019
On the Linear Speedup Analysis of Communication Efficient Momentum SGD for Distributed Non-Convex Optimization Hao Yu Rong Jin Sen Yang FedML 61 381 0 09 May 2019
Asynchronous Federated Optimization Cong Xie Oluwasanmi Koyejo Indranil Gupta FedML 47 564 0 10 Mar 2019
Robust and Communication-Efficient Federated Learning from Non-IID Data Felix Sattler Simon Wiedemann K. Müller Wojciech Samek FedML 41 1,343 0 07 Mar 2019
Agnostic Federated Learning M. Mohri Gary Sivek A. Suresh FedML 82 928 0 01 Feb 2019
Expanding the Reach of Federated Learning by Reducing Client Resource Requirements S. Caldas Jakub Konecný H. B. McMahan Ameet Talwalkar 52 449 0 18 Dec 2018
Federated Optimization in Heterogeneous Networks Tian Li Anit Kumar Sahu Manzil Zaheer Maziar Sanjabi Ameet Talwalkar Virginia Smith FedML 83 5,105 0 14 Dec 2018
Cooperative SGD: A unified Framework for the Design and Analysis of Communication-Efficient SGD Algorithms Jianyu Wang Gauri Joshi 93 348 0 22 Aug 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 55 602 0 17 Jul 2018
Local SGD Converges Fast and Communicates Little Sebastian U. Stich FedML 150 1,056 0 24 May 2018
Client Selection for Federated Learning with Heterogeneous Resources in Mobile Edge Takayuki Nishio Ryo Yonetani FedML 97 1,390 0 23 Apr 2018
Adaptive Federated Learning in Resource Constrained Edge Computing Systems Shiqiang Wang Tiffany Tuor Theodoros Salonidis K. Leung C. Makaya T. He Kevin S. Chan 200 1,692 0 14 Apr 2018
Federated Meta-Learning with Fast Convergence and Efficient Communication Fei Chen Mi Luo Zhenhua Dong Zhenguo Li Xiuqiang He FedML 56 395 0 22 Feb 2018
Differentially Private Federated Learning: A Client Level Perspective Robin C. Geyer T. Klein Moin Nabi FedML 85 1,287 0 20 Dec 2017
Safe Adaptive Importance Sampling Sebastian U. Stich Anant Raj Martin Jaggi 54 54 0 07 Nov 2017
On the convergence properties of a $K$ -step averaging stochastic gradient descent algorithm for nonconvex optimization Fan Zhou Guojing Cong 112 233 0 03 Aug 2017
Federated Multi-Task Learning Virginia Smith Chao-Kai Chiang Maziar Sanjabi Ameet Talwalkar FedML 83 1,791 0 30 May 2017
Federated Learning: Strategies for Improving Communication Efficiency Jakub Konecný H. B. McMahan Felix X. Yu Peter Richtárik A. Suresh Dave Bacon FedML 267 4,620 0 18 Oct 2016
Communication-Efficient Learning of Deep Networks from Decentralized Data H. B. McMahan Eider Moore Daniel Ramage S. Hampson Blaise Agüera y Arcas FedML 226 17,235 0 17 Feb 2016
Variance Reduction in SGD by Distributed Importance Sampling Guillaume Alain Alex Lamb Chinnadhurai Sankar Aaron Courville Yoshua Bengio FedML 44 198 0 20 Nov 2015
Stochastic Optimization with Importance Sampling P. Zhao Tong Zhang 57 343 0 13 Jan 2014
On the Learning Behavior of Adaptive Networks - Part I: Transient Analysis Jianshu Chen Ali H. Sayed 73 132 0 29 Dec 2013
Stochastic Gradient Descent, Weighted Sampling, and the Randomized Kaczmarz algorithm Deanna Needell Nathan Srebro Rachel A. Ward 94 551 0 21 Oct 2013
Distributed Delayed Stochastic Optimization Alekh Agarwal John C. Duchi 102 626 0 28 Apr 2011