Expanding the Reach of Federated Learning by Reducing Client Resource Requirements

18 December 2018

Papers citing "Expanding the Reach of Federated Learning by Reducing Client Resource Requirements"

22 / 22 papers shown

Title
FedSAUC: A Similarity-Aware Update Control for Communication-Efficient Federated Learning in Edge Computing Ming-Lun Lee Han-Chang Chou Yan-AnnChen FedML 72 6 0 07 Apr 2025
Moss: Proxy Model-based Full-Weight Aggregation in Federated Learning with Heterogeneous Models Y. Cai Ziqi Zhang Ding Li Yao Guo Xiangqun Chen 136 0 0 13 Mar 2025
Efficient Federated Finetuning of Tiny Transformers with Resource-Constrained Devices Kilian Pfeiffer Mohamed Aboelenien Ahmed R. Khalili J. Henkel 53 1 0 12 Nov 2024
FedSPU: Personalized Federated Learning for Resource-constrained Devices with Stochastic Parameter Update Ziru Niu Hai Dong •. A. K. Qin 94 2 0 18 Mar 2024
LW-FedSSL: Resource-efficient Layer-wise Federated Self-supervised Learning Ye Lin Tun Chu Myaet Thwal Le Quang Huy Minh N. H. Nguyen Choong Seon Hong FedML 88 2 0 22 Jan 2024
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 125 218 0 08 Aug 2020
ATOMO: Communication-efficient Learning via Atomic Sparsification Hongyi Wang Scott Sievert Zachary B. Charles Shengchao Liu S. Wright Dimitris Papailiopoulos 67 353 0 11 Jun 2018
High-Accuracy Low-Precision Training Christopher De Sa Megan Leszczynski Jian Zhang Alana Marzoev Christopher R. Aberger K. Olukotun Christopher Ré 64 109 0 09 Mar 2018
Towards Accurate Binary Convolutional Neural Network Xiaofan Lin Cong Zhao Wei Pan MQ 77 644 0 30 Nov 2017
Federated Multi-Task Learning Virginia Smith Chao-Kai Chiang Maziar Sanjabi Ameet Talwalkar FedML 150 1,807 0 30 May 2017
EMNIST: an extension of MNIST to handwritten letters Gregory Cohen Saeed Afshar J. Tapson André van Schaik 63 720 0 17 Feb 2017
Randomized Distributed Mean Estimation: Accuracy vs Communication Jakub Konecný Peter Richtárik FedML 115 102 0 22 Nov 2016
CoCoA: A General Framework for Communication-Efficient Distributed Optimization Virginia Smith Simone Forte Chenxin Ma Martin Takáč Michael I. Jordan Martin Jaggi 68 273 0 07 Nov 2016
Distributed Mean Estimation with Limited Communication A. Suresh Felix X. Yu Sanjiv Kumar H. B. McMahan FedML 97 364 0 02 Nov 2016
Federated Learning: Strategies for Improving Communication Efficiency Jakub Konecný H. B. McMahan Felix X. Yu Peter Richtárik A. Suresh Dave Bacon FedML 293 4,642 0 18 Oct 2016
Federated Optimization: Distributed Machine Learning for On-Device Intelligence Jakub Konecný H. B. McMahan Daniel Ramage Peter Richtárik FedML 126 1,897 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
Communication-Efficient Learning of Deep Networks from Decentralized Data H. B. McMahan Eider Moore Daniel Ramage S. Hampson Blaise Agüera y Arcas FedML 392 17,453 0 17 Feb 2016
Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding Song Han Huizi Mao W. Dally 3DGS 253 8,832 0 01 Oct 2015
Learning both Weights and Connections for Efficient Neural Networks Song Han Jeff Pool J. Tran W. Dally CVBM 310 6,669 0 08 Jun 2015
Distilling the Knowledge in a Neural Network Geoffrey E. Hinton Oriol Vinyals J. Dean FedML 342 19,634 0 09 Mar 2015
Striving for Simplicity: The All Convolutional Net Jost Tobias Springenberg Alexey Dosovitskiy Thomas Brox Martin Riedmiller FAtt 246 4,667 0 21 Dec 2014