A Resource-Adaptive Approach for Federated Learning under
Resource-Constrained Environments

A Resource-Adaptive Approach for Federated Learning under Resource-Constrained Environments

19 June 2024

Papers citing "A Resource-Adaptive Approach for Federated Learning under Resource-Constrained Environments"

9 / 9 papers shown

Title
Cooperative Backdoor Attack in Decentralized Reinforcement Learning with Theoretical Guarantee Mengtong Gao Yifei Zou Zuyuan Zhang Xiuzhen Cheng Dongxiao Yu AAML 87 4 0 24 May 2024
Resource Allocation in Large Language Model Integrated 6G Vehicular Networks Chang Liu Jun Zhao 37 11 0 27 Mar 2024
Efficient Large Scale Language Modeling with Mixtures of Experts Mikel Artetxe Shruti Bhosale Naman Goyal Todor Mihaylov Myle Ott ... Jeff Wang Luke Zettlemoyer Mona T. Diab Zornitsa Kozareva Ves Stoyanov MoE 157 194 0 20 Dec 2021
HeteroFL: Computation and Communication Efficient Federated Learning for Heterogeneous Clients Enmao Diao Jie Ding Vahid Tarokh FedML 96 554 0 03 Oct 2020
GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding Dmitry Lepikhin HyoukJoong Lee Yuanzhong Xu Dehao Chen Orhan Firat Yanping Huang M. Krikun Noam M. Shazeer Zhiwen Chen MoE 86 1,156 0 30 Jun 2020
SplitFed: When Federated Learning Meets Split Learning Chandra Thapa Pathum Chamikara Mahawaga Arachchige S. Çamtepe Lichao Sun FedML 85 575 0 25 Apr 2020
Model Pruning Enables Efficient Federated Learning on Edge Devices Yuang Jiang Shiqiang Wang Victor Valls Bongjun Ko Wei-Han Lee Kin K. Leung Leandros Tassiulas 59 461 0 26 Sep 2019
Deep Gradient Compression: Reducing the Communication Bandwidth for Distributed Training Chengyue Wu Song Han Huizi Mao Yu Wang W. Dally 120 1,407 0 05 Dec 2017
Communication-Efficient Learning of Deep Networks from Decentralized Data H. B. McMahan Eider Moore Daniel Ramage S. Hampson Blaise Agüera y Arcas FedML 380 17,437 0 17 Feb 2016