Federated Learning of a Mixture of Global and Local Models

10 February 2020

Papers citing "Federated Learning of a Mixture of Global and Local Models"

23 / 23 papers shown

Title
Lazy But Effective: Collaborative Personalized Federated Learning with Heterogeneous Data Ljubomir Rokvic Panayiotis Danassis Boi Faltings FedML 124 0 0 05 May 2025
dFLMoE: Decentralized Federated Learning via Mixture of Experts for Medical Data Analysis Luyuan Xie Tianyu Luan Wenyuan Cai Guochen Yan Zhaoyu Chen Nan Xi Yuejian Fang Qingni Shen Zhonghai Wu Junsong Yuan FedML 216 0 0 13 Mar 2025
PeFLL: Personalized Federated Learning by Learning to Learn Jonathan Scott Hossein Zakerinia Christoph H. Lampert FedML 179 10 0 17 Jan 2025
pFedGPA: Diffusion-based Generative Parameter Aggregation for Personalized Federated Learning Jiahao Lai Jiaqiang Li Jian Xu Yanru Wu Boshi Tang Siqi Chen Yongfeng Huang Wenbo Ding Yang Li FedML 127 0 0 09 Sep 2024
Federated Learning over Connected Modes Dennis Grinwald Philipp Wiesner Shinichi Nakajima FedML 128 0 0 05 Mar 2024
ADEPT: Hierarchical Bayes Approach to Personalized Federated Unsupervised Learning Kaan Ozkara Bruce Huang Ruida Zhou Suhas Diggavi 158 0 0 19 Feb 2024
Variance Reduced Local SGD with Lower Communication Complexity Xian-Feng Liang Shuheng Shen Jingchang Liu Zhen Pan Enhong Chen Yifei Cheng FedML 78 153 0 30 Dec 2019
Federated Variance-Reduced Stochastic Gradient Descent with Robustness to Byzantine Attacks Zhaoxian Wu Qing Ling Tianyi Chen G. Giannakis FedML AAML 70 183 0 29 Dec 2019
Advances and Open Problems in Federated Learning Peter Kairouz H. B. McMahan Brendan Avent A. Bellet M. Bennis ... Zheng Xu Qiang Yang Felix X. Yu Han Yu Sen Zhao FedML AI4CE 185 6,229 0 10 Dec 2019
SCAFFOLD: Stochastic Controlled Averaging for Federated Learning Sai Praneeth Karimireddy Satyen Kale M. Mohri Sashank J. Reddi Sebastian U. Stich A. Suresh FedML 65 346 0 14 Oct 2019
Tighter Theory for Local SGD on Identical and Heterogeneous Data Ahmed Khaled Konstantin Mishchenko Peter Richtárik 68 433 0 10 Sep 2019
First Analysis of Local GD on Heterogeneous Data Ahmed Khaled Konstantin Mishchenko Peter Richtárik FedML 60 172 0 10 Sep 2019
One Method to Rule Them All: Variance Reduction for Data, Parameters and Many New Methods Filip Hanzely Peter Richtárik 73 26 0 27 May 2019
A Unified Theory of SGD: Variance Reduction, Sampling, Quantization and Coordinate Descent Eduard A. Gorbunov Filip Hanzely Peter Richtárik 96 146 0 27 May 2019
Don't Jump Through Hoops and Remove Those Loops: SVRG and Katyusha are Better Without the Outer Loop D. Kovalev Samuel Horváth Peter Richtárik 77 156 0 24 Jan 2019
Local SGD Converges Fast and Communicates Little Sebastian U. Stich FedML 164 1,061 0 24 May 2018
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 803 11,866 0 09 Mar 2017
Federated Learning: Strategies for Improving Communication Efficiency Jakub Konecný H. B. McMahan Felix X. Yu Peter Richtárik A. Suresh Dave Bacon FedML 286 4,636 0 18 Oct 2016
Federated Optimization: Distributed Machine Learning for On-Device Intelligence Jakub Konecný H. B. McMahan Daniel Ramage Peter Richtárik FedML 124 1,895 0 08 Oct 2016
AIDE: Fast and Communication Efficient Distributed Optimization Sashank J. Reddi Jakub Konecný Peter Richtárik Barnabás Póczós Alex Smola 53 151 0 24 Aug 2016
SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly Convex Composite Objectives Aaron Defazio Francis R. Bach Simon Lacoste-Julien ODL 128 1,823 0 01 Jul 2014
A Proximal Stochastic Gradient Method with Progressive Variance Reduction Lin Xiao Tong Zhang ODL 147 738 0 19 Mar 2014
Parallel Coordinate Descent Methods for Big Data Optimization Peter Richtárik Martin Takáč 111 487 0 04 Dec 2012