Randomized Distributed Mean Estimation: Accuracy vs Communication

22 November 2016

Papers citing "Randomized Distributed Mean Estimation: Accuracy vs Communication"

24 / 24 papers shown

Title
SacFL: Self-Adaptive Federated Continual Learning for Resource-Constrained End Devices Zhengyi Zhong Weidong Bao Ji Wang Jianguo Chen Lingjuan Lyu Wei Yang Bryan Lim CLL 46 0 0 01 May 2025
Efficient Unbiased Sparsification Leighton Barnes Timothy Chow Emma Cohen Keith Frankston Benjamin Howard Fred Kochman Daniel Scheinerman Jeffrey VanderKam OT 37 1 0 22 Feb 2024
Kimad: Adaptive Gradient Compression with Bandwidth Awareness Jihao Xin Ivan Ilin Shunkang Zhang Marco Canini Peter Richtárik 37 2 0 13 Dec 2023
FedDIP: Federated Learning with Extreme Dynamic Pruning and Incremental Regularization Qianyu Long Christos Anagnostopoulos S. P. Parambath Daning Bi AI4CE FedML 23 2 0 13 Sep 2023
DoCoFL: Downlink Compression for Cross-Device Federated Learning Ron Dorfman S. Vargaftik Y. Ben-Itzhak Kfir Y. Levy FedML 32 18 0 01 Feb 2023
CEDAS: A Compressed Decentralized Stochastic Gradient Method with Improved Convergence Kun-Yen Huang Shin-Yi Pu 35 9 0 14 Jan 2023
Adaptive Compression for Communication-Efficient Distributed Training Maksim Makarenko Elnur Gasanov Rustem Islamov Abdurakhmon Sadiev Peter Richtárik 36 12 0 31 Oct 2022
Federated Learning Under Intermittent Client Availability and Time-Varying Communication Constraints Mónica Ribero H. Vikalo G. Veciana FedML 24 42 0 13 May 2022
Wyner-Ziv Gradient Compression for Federated Learning Kai Liang Huiru Zhong Haoning Chen Youlong Wu FedML 23 8 0 16 Nov 2021
Bristle: Decentralized Federated Learning in Byzantine, Non-i.i.d. Environments Joost Verbraeken M. Vos J. Pouwelse 31 4 0 21 Oct 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
Communication-Efficient Federated Learning with Binary Neural Networks YuZhi Yang Zhaoyang Zhang Qianqian Yang FedML 32 31 0 05 Oct 2021
EDEN: Communication-Efficient and Robust Distributed Mean Estimation for Federated Learning S. Vargaftik Ran Ben-Basat Amit Portnoy Gal Mendelson Y. Ben-Itzhak Michael Mitzenmacher FedML 46 45 0 19 Aug 2021
Slashing Communication Traffic in Federated Learning by Transmitting Clustered Model Updates Laizhong Cui Xiaoxin Su Yipeng Zhou Yi Pan FedML 38 36 0 10 May 2021
MARINA: Faster Non-Convex Distributed Learning with Compression Eduard A. Gorbunov Konstantin Burlachenko Zhize Li Peter Richtárik 39 109 0 15 Feb 2021
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
Optimal Client Sampling for Federated Learning Wenlin Chen Samuel Horváth Peter Richtárik FedML 42 191 0 26 Oct 2020
Optimization for Supervised Machine Learning: Randomized Algorithms for Data and Parameters Filip Hanzely 34 0 0 26 Aug 2020
Uncertainty Principle for Communication Compression in Distributed and Federated Learning and the Search for an Optimal Compressor M. Safaryan Egor Shulgin Peter Richtárik 29 60 0 20 Feb 2020
Federated Learning over Wireless Fading Channels M. Amiri Deniz Gunduz 33 507 0 23 Jul 2019
Natural Compression for Distributed Deep Learning Samuel Horváth Chen-Yu Ho L. Horvath Atal Narayan Sahu Marco Canini Peter Richtárik 21 151 0 27 May 2019
cpSGD: Communication-efficient and differentially-private distributed SGD Naman Agarwal A. Suresh Felix X. Yu Sanjiv Kumar H. B. McMahan FedML 25 485 0 27 May 2018
Gradient Sparsification for Communication-Efficient Distributed Optimization Jianqiao Wangni Jialei Wang Ji Liu Tong Zhang 15 522 0 26 Oct 2017
Distributed Mean Estimation with Limited Communication A. Suresh Felix X. Yu Sanjiv Kumar H. B. McMahan FedML 22 360 0 02 Nov 2016