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Variance-based Gradient Compression for Efficient Distributed Deep
  Learning

Variance-based Gradient Compression for Efficient Distributed Deep Learning

16 February 2018
Yusuke Tsuzuku
H. Imachi
Takuya Akiba
    FedML
ArXivPDFHTML

Papers citing "Variance-based Gradient Compression for Efficient Distributed Deep Learning"

12 / 12 papers shown
Title
Advances in APPFL: A Comprehensive and Extensible Federated Learning Framework
Advances in APPFL: A Comprehensive and Extensible Federated Learning Framework
Zilinghan Li
Shilan He
Ze Yang
Minseok Ryu
Kibaek Kim
Ravi K. Madduri
FedML
66
7
0
17 Sep 2024
RS-DGC: Exploring Neighborhood Statistics for Dynamic Gradient
  Compression on Remote Sensing Image Interpretation
RS-DGC: Exploring Neighborhood Statistics for Dynamic Gradient Compression on Remote Sensing Image Interpretation
Weiying Xie
Zixuan Wang
Jitao Ma
Daixun Li
Yunsong Li
40
0
0
29 Dec 2023
M22: A Communication-Efficient Algorithm for Federated Learning Inspired
  by Rate-Distortion
M22: A Communication-Efficient Algorithm for Federated Learning Inspired by Rate-Distortion
Yangyi Liu
Stefano Rini
Sadaf Salehkalaibar
Jun Chen
FedML
21
4
0
23 Jan 2023
Similarity-based Label Inference Attack against Training and Inference
  of Split Learning
Similarity-based Label Inference Attack against Training and Inference of Split Learning
Junlin Liu
Xinchen Lyu
Qimei Cui
Xiaofeng Tao
FedML
35
26
0
10 Mar 2022
BEAS: Blockchain Enabled Asynchronous & Secure Federated Machine
  Learning
BEAS: Blockchain Enabled Asynchronous & Secure Federated Machine Learning
A. Mondal
Harpreet Virk
Debayan Gupta
45
15
0
06 Feb 2022
On the Utility of Gradient Compression in Distributed Training Systems
On the Utility of Gradient Compression in Distributed Training Systems
Saurabh Agarwal
Hongyi Wang
Shivaram Venkataraman
Dimitris Papailiopoulos
41
46
0
28 Feb 2021
PSO-PS: Parameter Synchronization with Particle Swarm Optimization for
  Distributed Training of Deep Neural Networks
PSO-PS: Parameter Synchronization with Particle Swarm Optimization for Distributed Training of Deep Neural Networks
Qing Ye
Y. Han
Yanan Sun
Jiancheng Lv
28
3
0
06 Sep 2020
Federated Learning over Wireless Fading Channels
Federated Learning over Wireless Fading Channels
M. Amiri
Deniz Gunduz
33
508
0
23 Jul 2019
Deep Leakage from Gradients
Deep Leakage from Gradients
Ligeng Zhu
Zhijian Liu
Song Han
FedML
43
2,163
0
21 Jun 2019
Robust and Communication-Efficient Federated Learning from Non-IID Data
Robust and Communication-Efficient Federated Learning from Non-IID Data
Felix Sattler
Simon Wiedemann
K. Müller
Wojciech Samek
FedML
24
1,337
0
07 Mar 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
486
0
27 May 2018
Sparse Binary Compression: Towards Distributed Deep Learning with
  minimal Communication
Sparse Binary Compression: Towards Distributed Deep Learning with minimal Communication
Felix Sattler
Simon Wiedemann
K. Müller
Wojciech Samek
MQ
36
212
0
22 May 2018
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