Decentralized Deep Learning with Arbitrary Communication Compression

Decentralized Deep Learning with Arbitrary Communication Compression

22 July 2019

Anastasia Koloskova

Sebastian U. Stich

Papers citing "Decentralized Deep Learning with Arbitrary Communication Compression"

11 / 61 papers shown

Title
Periodic Stochastic Gradient Descent with Momentum for Decentralized Training Hongchang Gao Heng-Chiao Huang 20 25 0 24 Aug 2020
PowerGossip: Practical Low-Rank Communication Compression in Decentralized Deep Learning Thijs Vogels Sai Praneeth Karimireddy Martin Jaggi FedML 9 54 0 04 Aug 2020
Federated Learning with Compression: Unified Analysis and Sharp Guarantees Farzin Haddadpour Mohammad Mahdi Kamani Aryan Mokhtari M. Mahdavi FedML 33 271 0 02 Jul 2020
Optimal Complexity in Decentralized Training Yucheng Lu Christopher De Sa 38 72 0 15 Jun 2020
Communication-Efficient Distributed Stochastic AUC Maximization with Deep Neural Networks Zhishuai Guo Mingrui Liu Zhuoning Yuan Li Shen Wei Liu Tianbao Yang 33 42 0 05 May 2020
Detached Error Feedback for Distributed SGD with Random Sparsification An Xu Heng-Chiao Huang 36 9 0 11 Apr 2020
A Unified Theory of Decentralized SGD with Changing Topology and Local Updates Anastasia Koloskova Nicolas Loizou Sadra Boreiri Martin Jaggi Sebastian U. Stich FedML 41 493 0 23 Mar 2020
Q-GADMM: Quantized Group ADMM for Communication Efficient Decentralized Machine Learning Anis Elgabli Jihong Park Amrit Singh Bedi Chaouki Ben Issaid M. Bennis Vaneet Aggarwal 24 67 0 23 Oct 2019
Clustered Federated Learning: Model-Agnostic Distributed Multi-Task Optimization under Privacy Constraints Felix Sattler K. Müller Wojciech Samek FedML 45 966 0 04 Oct 2019
Gradient Descent with Compressed Iterates Ahmed Khaled Peter Richtárik 21 22 0 10 Sep 2019
Optimal Distributed Online Prediction using Mini-Batches O. Dekel Ran Gilad-Bachrach Ohad Shamir Lin Xiao 177 683 0 07 Dec 2010