A Double Residual Compression Algorithm for Efficient Distributed
Learning

A Double Residual Compression Algorithm for Efficient Distributed Learning

16 October 2019

Xiaorui Liu

Papers citing "A Double Residual Compression Algorithm for Efficient Distributed Learning"

14 / 14 papers shown

Title
LoCoDL: Communication-Efficient Distributed Learning with Local Training and Compression Laurent Condat A. Maranjyan Peter Richtárik 49 4 0 07 Mar 2024
ELF: Federated Langevin Algorithms with Primal, Dual and Bidirectional Compression Avetik G. Karagulyan Peter Richtárik FedML 34 6 0 08 Mar 2023
DoCoFL: Downlink Compression for Cross-Device Federated Learning Ron Dorfman S. Vargaftik Y. Ben-Itzhak Kfir Y. Levy FedML 34 19 0 01 Feb 2023
Analysis of Error Feedback in Federated Non-Convex Optimization with Biased Compression Xiaoyun Li Ping Li FedML 36 4 0 25 Nov 2022
Downlink Compression Improves TopK Sparsification William Zou H. Sterck Jun Liu 21 0 0 30 Sep 2022
ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction Keshav Santhanam Omar Khattab Jon Saad-Falcon Christopher Potts Matei A. Zaharia 39 385 0 02 Dec 2021
Basis Matters: Better Communication-Efficient Second Order Methods for Federated Learning Xun Qian Rustem Islamov M. Safaryan Peter Richtárik FedML 24 23 0 02 Nov 2021
Leveraging Spatial and Temporal Correlations in Sparsified Mean Estimation Divyansh Jhunjhunwala Ankur Mallick Advait Gadhikar S. Kadhe Gauri Joshi 24 10 0 14 Oct 2021
ProgFed: Effective, Communication, and Computation Efficient Federated Learning by Progressive Training Hui-Po Wang Sebastian U. Stich Yang He Mario Fritz FedML AI4CE 36 46 0 11 Oct 2021
Decentralized Composite Optimization with Compression Yao Li Xiaorui Liu Jiliang Tang Ming Yan Kun Yuan 27 9 0 10 Aug 2021
ErrorCompensatedX: error compensation for variance reduced algorithms Hanlin Tang Yao Li Ji Liu Ming Yan 32 10 0 04 Aug 2021
Communication-Efficient Federated Learning via Predictive Coding Kai Yue Richeng Jin Chau-Wai Wong H. Dai FedML 25 14 0 02 Aug 2021
FedNL: Making Newton-Type Methods Applicable to Federated Learning M. Safaryan Rustem Islamov Xun Qian Peter Richtárik FedML 33 78 0 05 Jun 2021
Federated Learning via Synthetic Data Jack Goetz Ambuj Tewari FedML DD 27 71 0 11 Aug 2020