Optimizing the Communication-Accuracy Trade-off in Federated Learning
with Rate-Distortion Theory

Optimizing the Communication-Accuracy Trade-off in Federated Learning with Rate-Distortion Theory

7 January 2022

Nicole Mitchell

Johannes Ballé

Zachary B. Charles

Papers citing "Optimizing the Communication-Accuracy Trade-off in Federated Learning with Rate-Distortion Theory"

18 / 18 papers shown

Title
PRISM: Privacy-Preserving Improved Stochastic Masking for Federated Generative Models Kyeongkook Seo Dong-Jun Han Jaejun Yoo 45 0 0 11 Mar 2025
Theoretical Analysis of Privacy Leakage in Trustworthy Federated Learning: A Perspective from Linear Algebra and Optimization Theory Xiaojin Zhang Wei Chen FedML 39 0 0 23 Jul 2024
Improved Communication-Privacy Trade-offs in $L_2$ Mean Estimation under Streaming Differential Privacy Wei-Ning Chen Berivan Isik Peter Kairouz Albert No Sewoong Oh Zheng Xu 57 3 0 02 May 2024
Federated Learning: Attacks, Defenses, Opportunities, and Challenges Ghazaleh Shirvani Saeid Ghasemshirazi Behzad Beigzadeh FedML 57 3 0 10 Mar 2024
Joint Compression and Deadline Optimization for Wireless Federated Learning Maojun Zhang Yong Li Dongzhu Liu Richeng Jin Guangxu Zhu Caijun Zhong Tony Q. S. Quek 29 5 0 06 May 2023
Federated Automatic Differentiation Keith Rush Zachary B. Charles Zachary Garrett FedML 34 1 0 18 Jan 2023
ResFed: Communication Efficient Federated Learning by Transmitting Deep Compressed Residuals Rui Song Liguo Zhou Lingjuan Lyu Andreas Festag Alois Knoll FedML 32 5 0 11 Dec 2022
Sparse Random Networks for Communication-Efficient Federated Learning Berivan Isik Francesco Pase Deniz Gunduz Tsachy Weissman M. Zorzi FedML 70 52 0 30 Sep 2022
Federated Select: A Primitive for Communication- and Memory-Efficient Federated Learning Zachary B. Charles Kallista A. Bonawitz Stanislav Chiknavaryan H. B. McMahan Blaise Agüera y Arcas FedML 23 13 0 19 Aug 2022
Mixed Federated Learning: Joint Decentralized and Centralized Learning S. Augenstein Andrew Straiton Hard Lin Ning K. Singhal Satyen Kale Kurt Partridge Rajiv Mathews FedML 38 8 0 26 May 2022
QUIC-FL: Quick Unbiased Compression for Federated Learning Ran Ben-Basat S. Vargaftik Amit Portnoy Gil Einziger Y. Ben-Itzhak Michael Mitzenmacher FedML 69 13 0 26 May 2022
Correlated quantization for distributed mean estimation and optimization A. Suresh Ziteng Sun Jae Hun Ro Felix X. Yu 23 12 0 09 Mar 2022
Linear Stochastic Bandits over a Bit-Constrained Channel A. Mitra Hamed Hassani George J. Pappas 39 8 0 02 Mar 2022
Papaya: Practical, Private, and Scalable Federated Learning Dzmitry Huba John Nguyen Kshitiz Malik Ruiyu Zhu Michael G. Rabbat ... H. Srinivas Kaikai Wang Anthony Shoumikhin Jesik Min Mani Malek FedML 113 137 0 08 Nov 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
DRIVE: One-bit Distributed Mean Estimation S. Vargaftik Ran Ben-Basat Amit Portnoy Gal Mendelson Y. Ben-Itzhak Michael Mitzenmacher OOD FedML 82 51 0 18 May 2021
IBM Federated Learning: an Enterprise Framework White Paper V0.1 Heiko Ludwig Nathalie Baracaldo Gegi Thomas Yi Zhou Ali Anwar ... Sean Laguna Mikhail Yurochkin Mayank Agarwal Ebube Chuba Annie Abay FedML 131 157 0 22 Jul 2020
FedPAQ: A Communication-Efficient Federated Learning Method with Periodic Averaging and Quantization Amirhossein Reisizadeh Aryan Mokhtari Hamed Hassani Ali Jadbabaie Ramtin Pedarsani FedML 174 760 0 28 Sep 2019