ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1611.07555
  4. Cited By
Randomized Distributed Mean Estimation: Accuracy vs Communication

Randomized Distributed Mean Estimation: Accuracy vs Communication

22 November 2016
Jakub Konecný
Peter Richtárik
    FedML
ArXivPDFHTML

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

26 / 26 papers shown
Title
SacFL: Self-Adaptive Federated Continual Learning for Resource-Constrained End Devices
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
Communication-Efficient Large-Scale Distributed Deep Learning: A
  Comprehensive Survey
Communication-Efficient Large-Scale Distributed Deep Learning: A Comprehensive Survey
Feng Liang
Zhen Zhang
Haifeng Lu
Victor C. M. Leung
Yanyi Guo
Xiping Hu
GNN
37
6
0
09 Apr 2024
Efficient Unbiased Sparsification
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
Kimad: Adaptive Gradient Compression with Bandwidth Awareness
Jihao Xin
Ivan Ilin
Shunkang Zhang
Marco Canini
Peter Richtárik
37
3
0
13 Dec 2023
Fundamental Limits of Distributed Optimization over Multiple Access
  Channel
Fundamental Limits of Distributed Optimization over Multiple Access Channel
Shubham K. Jha
17
1
0
05 Oct 2023
FedDIP: Federated Learning with Extreme Dynamic Pruning and Incremental
  Regularization
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
DoCoFL: Downlink Compression for Cross-Device Federated Learning
Ron Dorfman
S. Vargaftik
Y. Ben-Itzhak
Kfir Y. Levy
FedML
32
19
0
01 Feb 2023
CEDAS: A Compressed Decentralized Stochastic Gradient Method with
  Improved Convergence
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
Adaptive Compression for Communication-Efficient Distributed Training
Maksim Makarenko
Elnur Gasanov
Rustem Islamov
Abdurakhmon Sadiev
Peter Richtárik
39
12
0
31 Oct 2022
Federated Learning Under Intermittent Client Availability and
  Time-Varying Communication Constraints
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
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
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
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
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
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
46
0
19 Aug 2021
Slashing Communication Traffic in Federated Learning by Transmitting
  Clustered Model Updates
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
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
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
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
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
Uncertainty Principle for Communication Compression in Distributed and Federated Learning and the Search for an Optimal Compressor
M. Safaryan
Egor Shulgin
Peter Richtárik
32
60
0
20 Feb 2020
Federated Learning over Wireless Fading Channels
Federated Learning over Wireless Fading Channels
M. Amiri
Deniz Gunduz
33
507
0
23 Jul 2019
Natural Compression for Distributed Deep Learning
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
cpSGD: Communication-efficient and differentially-private distributed SGD
Naman Agarwal
A. Suresh
Felix X. Yu
Sanjiv Kumar
H. B. McMahan
FedML
28
485
0
27 May 2018
Gradient Sparsification for Communication-Efficient Distributed
  Optimization
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
Distributed Mean Estimation with Limited Communication
A. Suresh
Felix X. Yu
Sanjiv Kumar
H. B. McMahan
FedML
22
360
0
02 Nov 2016
1