Distributed Deep Learning with Event-Triggered Communication

8 September 2019

Papers citing "Distributed Deep Learning with Event-Triggered Communication"

12 / 12 papers shown

Title
MATCHA: Speeding Up Decentralized SGD via Matching Decomposition Sampling Jianyu Wang Anit Kumar Sahu Zhouyi Yang Gauri Joshi S. Kar 65 163 0 23 May 2019
On Nonconvex Optimization for Machine Learning: Gradients, Stochasticity, and Saddle Points Chi Jin Praneeth Netrapalli Rong Ge Sham Kakade Michael I. Jordan 79 61 0 13 Feb 2019
Sharp Analysis for Nonconvex SGD Escaping from Saddle Points Cong Fang Zhouchen Lin Tong Zhang 71 104 0 01 Feb 2019
Stochastic Gradient Push for Distributed Deep Learning Mahmoud Assran Nicolas Loizou Nicolas Ballas Michael G. Rabbat 79 346 0 27 Nov 2018
Cooperative SGD: A unified Framework for the Design and Analysis of Communication-Efficient SGD Algorithms Jianyu Wang Gauri Joshi 168 349 0 22 Aug 2018
Distributed Stochastic Gradient Tracking Methods Shi Pu A. Nedić 64 291 0 25 May 2018
D $^2$ : Decentralized Training over Decentralized Data Hanlin Tang Xiangru Lian Ming Yan Ce Zhang Ji Liu 37 350 0 19 Mar 2018
Collaborative Deep Learning in Fixed Topology Networks Zhanhong Jiang Aditya Balu Chinmay Hegde Soumik Sarkar FedML 59 180 0 23 Jun 2017
Federated Learning: Strategies for Improving Communication Efficiency Jakub Konecný H. B. McMahan Felix X. Yu Peter Richtárik A. Suresh Dave Bacon FedML 306 4,646 0 18 Oct 2016
NEXT: In-Network Nonconvex Optimization P. Lorenzo G. Scutari 103 508 0 01 Feb 2016
Parallel and Distributed Methods for Nonconvex Optimization--Part II: Applications G. Scutari F. Facchinei Lorenzo Lampariello Peiran Song Stefania Sardellitti 42 258 0 15 Jan 2016
HOGWILD!: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent Feng Niu Benjamin Recht Christopher Ré Stephen J. Wright 198 2,273 0 28 Jun 2011