M22: A Communication-Efficient Algorithm for Federated Learning Inspired
by Rate-Distortion

M22: A Communication-Efficient Algorithm for Federated Learning Inspired by Rate-Distortion

23 January 2023

Sadaf Salehkalaibar

Jun Chen

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Papers citing "M22: A Communication-Efficient Algorithm for Federated Learning Inspired by Rate-Distortion"

14 / 14 papers shown

Title
An Information-Theoretic Justification for Model Pruning Berivan Isik Tsachy Weissman Albert No 129 36 0 16 Feb 2021
Layer-adaptive sparsity for the Magnitude-based Pruning Jaeho Lee Sejun Park Sangwoo Mo SungSoo Ahn Jinwoo Shin 89 203 0 15 Oct 2020
FetchSGD: Communication-Efficient Federated Learning with Sketching D. Rothchild Ashwinee Panda Enayat Ullah Nikita Ivkin Ion Stoica Vladimir Braverman Joseph E. Gonzalez Raman Arora FedML 79 370 0 15 Jul 2020
Approximate Inference Turns Deep Networks into Gaussian Processes Mohammad Emtiyaz Khan Alexander Immer Ehsan Abedi M. Korzepa UQCV BDL 108 125 0 05 Jun 2019
A mean-field limit for certain deep neural networks Dyego Araújo R. Oliveira Daniel Yukimura AI4CE 66 70 0 01 Jun 2019
Robust and Communication-Efficient Federated Learning from Non-IID Data Felix Sattler Simon Wiedemann K. Müller Wojciech Samek FedML 74 1,362 0 07 Mar 2019
Gaussian Process Behaviour in Wide Deep Neural Networks A. G. Matthews Mark Rowland Jiri Hron Richard Turner Zoubin Ghahramani BDL 157 561 0 30 Apr 2018
A Mean Field View of the Landscape of Two-Layers Neural Networks Song Mei Andrea Montanari Phan-Minh Nguyen MLT 105 862 0 18 Apr 2018
Deep Gradient Compression: Reducing the Communication Bandwidth for Distributed Training Chengyue Wu Song Han Huizi Mao Yu Wang W. Dally 148 1,409 0 05 Dec 2017
Deep Neural Networks as Gaussian Processes Jaehoon Lee Yasaman Bahri Roman Novak S. Schoenholz Jeffrey Pennington Jascha Narain Sohl-Dickstein UQCV BDL 135 1,099 0 01 Nov 2017
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms Han Xiao Kashif Rasul Roland Vollgraf 285 8,926 0 25 Aug 2017
TernGrad: Ternary Gradients to Reduce Communication in Distributed Deep Learning W. Wen Cong Xu Feng Yan Chunpeng Wu Yandan Wang Yiran Chen Hai Helen Li 163 990 0 22 May 2017
Sparse Communication for Distributed Gradient Descent Alham Fikri Aji Kenneth Heafield 76 741 0 17 Apr 2017
Federated Learning: Strategies for Improving Communication Efficiency Jakub Konecný H. B. McMahan Felix X. Yu Peter Richtárik A. Suresh Dave Bacon FedML 309 4,655 0 18 Oct 2016

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