Decentralized Stochastic Optimization and Gossip Algorithms with Compressed Communication

1 February 2019

Papers citing "Decentralized Stochastic Optimization and Gossip Algorithms with Compressed Communication"

47 / 97 papers shown

Title
Decentralized Composite Optimization with Compression Yao Li Xiaorui Liu Jiliang Tang Ming Yan Kun Yuan 27 9 0 10 Aug 2021
Decentralized Federated Learning: Balancing Communication and Computing Costs Wei Liu Li Chen Wenyi Zhang FedML 19 106 0 26 Jul 2021
A Field Guide to Federated Optimization Jianyu Wang Zachary B. Charles Zheng Xu Gauri Joshi H. B. McMahan ... Mi Zhang Tong Zhang Chunxiang Zheng Chen Zhu Wennan Zhu FedML 187 412 0 14 Jul 2021
BAGUA: Scaling up Distributed Learning with System Relaxations Shaoduo Gan Xiangru Lian Rui Wang Jianbin Chang Chengjun Liu ... Jiawei Jiang Binhang Yuan Sen Yang Ji Liu Ce Zhang 25 30 0 03 Jul 2021
ResIST: Layer-Wise Decomposition of ResNets for Distributed Training Chen Dun Cameron R. Wolfe C. Jermaine Anastasios Kyrillidis 16 21 0 02 Jul 2021
The Values Encoded in Machine Learning Research Abeba Birhane Pratyusha Kalluri Dallas Card William Agnew Ravit Dotan Michelle Bao 38 274 0 29 Jun 2021
Decentralized Constrained Optimization: Double Averaging and Gradient Projection Firooz Shahriari-Mehr David Bosch Ashkan Panahi 16 8 0 21 Jun 2021
Decentralized Local Stochastic Extra-Gradient for Variational Inequalities Aleksandr Beznosikov Pavel Dvurechensky Anastasia Koloskova V. Samokhin Sebastian U. Stich Alexander Gasnikov 32 43 0 15 Jun 2021
PPT: A Privacy-Preserving Global Model Training Protocol for Federated Learning in P2P Networks Qian Chen Zilong Wang Wenjing Zhang Xiaodong Lin FedML 33 16 0 30 May 2021
Towards Demystifying Serverless Machine Learning Training Jiawei Jiang Shaoduo Gan Yue Liu Fanlin Wang Gustavo Alonso Ana Klimovic Ankit Singla Wentao Wu Ce Zhang 19 121 0 17 May 2021
Innovation Compression for Communication-efficient Distributed Optimization with Linear Convergence Jiaqi Zhang Keyou You Lihua Xie 8 32 0 14 May 2021
Regret and Cumulative Constraint Violation Analysis for Distributed Online Constrained Convex Optimization Xinlei Yi Xiuxian Li Tao Yang Lihua Xie Tianyou Chai Karl H. Johansson 13 39 0 01 May 2021
DataLens: Scalable Privacy Preserving Training via Gradient Compression and Aggregation Wei Ping Fan Wu Yunhui Long Luka Rimanic Ce Zhang Bo-wen Li FedML 45 63 0 20 Mar 2021
Moshpit SGD: Communication-Efficient Decentralized Training on Heterogeneous Unreliable Devices Max Ryabinin Eduard A. Gorbunov Vsevolod Plokhotnyuk Gennady Pekhimenko 35 32 0 04 Mar 2021
On the Utility of Gradient Compression in Distributed Training Systems Saurabh Agarwal Hongyi Wang Shivaram Venkataraman Dimitris Papailiopoulos 31 46 0 28 Feb 2021
Wirelessly Powered Federated Edge Learning: Optimal Tradeoffs Between Convergence and Power Transfer Qunsong Zeng Yuqing Du Kaibin Huang 37 35 0 24 Feb 2021
Communication-efficient Distributed Cooperative Learning with Compressed Beliefs Taha Toghani César A. Uribe 27 15 0 14 Feb 2021
Sparse-Push: Communication- & Energy-Efficient Decentralized Distributed Learning over Directed & Time-Varying Graphs with non-IID Datasets Sai Aparna Aketi Amandeep Singh J. Rabaey 29 10 0 10 Feb 2021
Consensus Control for Decentralized Deep Learning Lingjing Kong Tao R. Lin Anastasia Koloskova Martin Jaggi Sebastian U. Stich 19 76 0 09 Feb 2021
Federated Learning over Wireless Device-to-Device Networks: Algorithms and Convergence Analysis Hong Xing Osvaldo Simeone Suzhi Bi 45 92 0 29 Jan 2021
IPLS : A Framework for Decentralized Federated Learning C. Pappas Dimitris Chatzopoulos S. Lalis M. Vavalis VLM 27 66 0 06 Jan 2021
Decentralized Federated Learning via Mutual Knowledge Transfer Chengxi Li Gang Li P. Varshney FedML 26 106 0 24 Dec 2020
On the Benefits of Multiple Gossip Steps in Communication-Constrained Decentralized Optimization Abolfazl Hashemi Anish Acharya Rudrajit Das H. Vikalo Sujay Sanghavi Inderjit Dhillon 20 7 0 20 Nov 2020
A Linearly Convergent Algorithm for Decentralized Optimization: Sending Less Bits for Free! D. Kovalev Anastasia Koloskova Martin Jaggi Peter Richtárik Sebastian U. Stich 23 73 0 03 Nov 2020
Throughput-Optimal Topology Design for Cross-Silo Federated Learning Othmane Marfoq Chuan Xu Giovanni Neglia Richard Vidal FedML 67 85 0 23 Oct 2020
FedAT: A High-Performance and Communication-Efficient Federated Learning System with Asynchronous Tiers Zheng Chai Yujing Chen Ali Anwar Liang Zhao Yue Cheng Huzefa Rangwala FedML 26 122 0 12 Oct 2020
Sparse Communication for Training Deep Networks Negar Foroutan Martin Jaggi FedML 30 16 0 19 Sep 2020
On Communication Compression for Distributed Optimization on Heterogeneous Data Sebastian U. Stich 50 23 0 04 Sep 2020
Periodic Stochastic Gradient Descent with Momentum for Decentralized Training Hongchang Gao Heng-Chiao Huang 23 25 0 24 Aug 2020
PowerGossip: Practical Low-Rank Communication Compression in Decentralized Deep Learning Thijs Vogels Sai Praneeth Karimireddy Martin Jaggi FedML 11 54 0 04 Aug 2020
On stochastic mirror descent with interacting particles: convergence properties and variance reduction Anastasia Borovykh N. Kantas P. Parpas G. Pavliotis 28 12 0 15 Jul 2020
Robust Federated Learning: The Case of Affine Distribution Shifts Amirhossein Reisizadeh Farzan Farnia Ramtin Pedarsani Ali Jadbabaie FedML OOD 32 162 0 16 Jun 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
A Robust Gradient Tracking Method for Distributed Optimization over Directed Networks Shi Pu 29 38 0 31 Mar 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
Decentralized gradient methods: does topology matter? Giovanni Neglia Chuan Xu Don Towsley G. Calbi 16 50 0 28 Feb 2020
Gradient tracking and variance reduction for decentralized optimization and machine learning Ran Xin S. Kar U. Khan 19 10 0 13 Feb 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
Communication-Efficient Local Decentralized SGD Methods Xiang Li Wenhao Yang Shusen Wang Zhihua Zhang 30 53 0 21 Oct 2019
Robust Distributed Accelerated Stochastic Gradient Methods for Multi-Agent Networks Alireza Fallah Mert Gurbuzbalaban Asuman Ozdaglar Umut Simsekli Lingjiong Zhu 32 28 0 19 Oct 2019
Clustered Federated Learning: Model-Agnostic Distributed Multi-Task Optimization under Privacy Constraints Felix Sattler K. Müller Wojciech Samek FedML 69 966 0 04 Oct 2019
Gradient Descent with Compressed Iterates Ahmed Khaled Peter Richtárik 21 22 0 10 Sep 2019
Robust and Communication-Efficient Collaborative Learning Amirhossein Reisizadeh Hossein Taheri Aryan Mokhtari Hamed Hassani Ramtin Pedarsani 25 89 0 24 Jul 2019
Asymptotic Network Independence in Distributed Stochastic Optimization for Machine Learning Shi Pu Alexander Olshevsky I. Paschalidis 28 41 0 28 Jun 2019
MATCHA: Speeding Up Decentralized SGD via Matching Decomposition Sampling Jianyu Wang Anit Kumar Sahu Zhouyi Yang Gauri Joshi S. Kar 29 159 0 23 May 2019
Optimal Distributed Online Prediction using Mini-Batches O. Dekel Ran Gilad-Bachrach Ohad Shamir Lin Xiao 179 683 0 07 Dec 2010