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Deep Gradient Compression: Reducing the Communication Bandwidth for
  Distributed Training
v1v2v3 (latest)

Deep Gradient Compression: Reducing the Communication Bandwidth for Distributed Training

5 December 2017
Chengyue Wu
Song Han
Huizi Mao
Yu Wang
W. Dally
ArXiv (abs)PDFHTMLGithub (222★)

Papers citing "Deep Gradient Compression: Reducing the Communication Bandwidth for Distributed Training"

50 / 625 papers shown
Title
Auto-Precision Scaling for Distributed Deep Learning
Auto-Precision Scaling for Distributed Deep Learning
Ruobing Han
J. Demmel
Yang You
43
5
0
20 Nov 2019
Understanding Top-k Sparsification in Distributed Deep Learning
Understanding Top-k Sparsification in Distributed Deep Learning
Shaoshuai Shi
Xiaowen Chu
Ka Chun Cheung
Simon See
233
101
0
20 Nov 2019
Layer-wise Adaptive Gradient Sparsification for Distributed Deep
  Learning with Convergence Guarantees
Layer-wise Adaptive Gradient Sparsification for Distributed Deep Learning with Convergence Guarantees
Shaoshuai Shi
Zhenheng Tang
Qiang-qiang Wang
Kaiyong Zhao
Xiaowen Chu
65
22
0
20 Nov 2019
Distributed Machine Learning through Heterogeneous Edge Systems
Distributed Machine Learning through Heterogeneous Edge Systems
Han Hu
Dan Wang
Chuan Wu
71
43
0
16 Nov 2019
Hyper-Sphere Quantization: Communication-Efficient SGD for Federated
  Learning
Hyper-Sphere Quantization: Communication-Efficient SGD for Federated Learning
XINYAN DAI
Xiao Yan
Kaiwen Zhou
Han Yang
K. K. Ng
James Cheng
Yu Fan
FedML
68
47
0
12 Nov 2019
An Overview of Data-Importance Aware Radio Resource Management for Edge
  Machine Learning
An Overview of Data-Importance Aware Radio Resource Management for Edge Machine Learning
Dingzhu Wen
Xiaoyang Li
Qunsong Zeng
Jinke Ren
Kaibin Huang
65
25
0
10 Nov 2019
A Crowdsourcing Framework for On-Device Federated Learning
A Crowdsourcing Framework for On-Device Federated Learning
Shashi Raj Pandey
N. H. Tran
M. Bennis
Y. Tun
Aunas Manzoor
Choong Seon Hong
FedML
73
253
0
04 Nov 2019
On-Device Machine Learning: An Algorithms and Learning Theory
  Perspective
On-Device Machine Learning: An Algorithms and Learning Theory Perspective
Sauptik Dhar
Junyao Guo
Jiayi Liu
S. Tripathi
Unmesh Kurup
Mohak Shah
124
144
0
02 Nov 2019
Progressive Compressed Records: Taking a Byte out of Deep Learning Data
Progressive Compressed Records: Taking a Byte out of Deep Learning Data
Michael Kuchnik
George Amvrosiadis
Virginia Smith
75
9
0
01 Nov 2019
Robust Federated Learning with Noisy Communication
Robust Federated Learning with Noisy Communication
F. Ang
Li Chen
Senior Member Ieee Nan Zhao
Senior Member Ieee Yunfei Chen
Weidong Wang
Feng Yu
FedML
58
117
0
01 Nov 2019
SPARQ-SGD: Event-Triggered and Compressed Communication in Decentralized
  Stochastic Optimization
SPARQ-SGD: Event-Triggered and Compressed Communication in Decentralized Stochastic Optimization
Navjot Singh
Deepesh Data
Jemin George
Suhas Diggavi
88
23
0
31 Oct 2019
Local SGD with Periodic Averaging: Tighter Analysis and Adaptive
  Synchronization
Local SGD with Periodic Averaging: Tighter Analysis and Adaptive Synchronization
Farzin Haddadpour
Mohammad Mahdi Kamani
M. Mahdavi
V. Cadambe
FedML
87
202
0
30 Oct 2019
E2-Train: Training State-of-the-art CNNs with Over 80% Energy Savings
E2-Train: Training State-of-the-art CNNs with Over 80% Energy Savings
Yue Wang
Ziyu Jiang
Xiaohan Chen
Pengfei Xu
Yang Zhao
Yingyan Lin
Zhangyang Wang
MQ
112
83
0
29 Oct 2019
Shielding Collaborative Learning: Mitigating Poisoning Attacks through
  Client-Side Detection
Shielding Collaborative Learning: Mitigating Poisoning Attacks through Client-Side Detection
Lingchen Zhao
Shengshan Hu
Qian Wang
Jianlin Jiang
Chao Shen
Xiangyang Luo
Pengfei Hu
AAML
72
96
0
29 Oct 2019
Gradient Sparification for Asynchronous Distributed Training
Gradient Sparification for Asynchronous Distributed Training
Zijie Yan
FedML
26
1
0
24 Oct 2019
Communication-Efficient Local Decentralized SGD Methods
Communication-Efficient Local Decentralized SGD Methods
Xiang Li
Wenhao Yang
Shusen Wang
Zhihua Zhang
97
53
0
21 Oct 2019
Machine Learning Systems for Highly-Distributed and Rapidly-Growing Data
Machine Learning Systems for Highly-Distributed and Rapidly-Growing Data
Kevin Hsieh
SyDaOOD
38
4
0
18 Oct 2019
Election Coding for Distributed Learning: Protecting SignSGD against
  Byzantine Attacks
Election Coding for Distributed Learning: Protecting SignSGD against Byzantine Attacks
Jy-yong Sohn
Dong-Jun Han
Beongjun Choi
Jaekyun Moon
FedML
98
37
0
14 Oct 2019
Eavesdrop the Composition Proportion of Training Labels in Federated
  Learning
Eavesdrop the Composition Proportion of Training Labels in Federated Learning
Lixu Wang
Shichao Xu
Tianlin Li
Qi Zhu
FedML
83
63
0
14 Oct 2019
JSDoop and TensorFlow.js: Volunteer Distributed Web Browser-Based Neural
  Network Training
JSDoop and TensorFlow.js: Volunteer Distributed Web Browser-Based Neural Network Training
José Á. Morell
Andrés Camero
Enrique Alba
58
9
0
12 Oct 2019
Straggler-Agnostic and Communication-Efficient Distributed Primal-Dual
  Algorithm for High-Dimensional Data Mining
Straggler-Agnostic and Communication-Efficient Distributed Primal-Dual Algorithm for High-Dimensional Data Mining
Zhouyuan Huo
Heng-Chiao Huang
FedML
47
5
0
09 Oct 2019
Clustered Federated Learning: Model-Agnostic Distributed Multi-Task
  Optimization under Privacy Constraints
Clustered Federated Learning: Model-Agnostic Distributed Multi-Task Optimization under Privacy Constraints
Felix Sattler
K. Müller
Wojciech Samek
FedML
197
1,014
0
04 Oct 2019
Minimax Bounds for Distributed Logistic Regression
Minimax Bounds for Distributed Logistic Regression
Florent Chiaroni
N. Hueber
FedML
32
5
0
03 Oct 2019
The Non-IID Data Quagmire of Decentralized Machine Learning
The Non-IID Data Quagmire of Decentralized Machine Learning
Kevin Hsieh
Amar Phanishayee
O. Mutlu
Phillip B. Gibbons
192
575
0
01 Oct 2019
Model Pruning Enables Efficient Federated Learning on Edge Devices
Model Pruning Enables Efficient Federated Learning on Edge Devices
Yuang Jiang
Shiqiang Wang
Victor Valls
Bongjun Ko
Wei-Han Lee
Kin K. Leung
Leandros Tassiulas
160
470
0
26 Sep 2019
Communication-Efficient Distributed Learning via Lazily Aggregated
  Quantized Gradients
Communication-Efficient Distributed Learning via Lazily Aggregated Quantized Gradients
Jun Sun
Tianyi Chen
G. Giannakis
Zaiyue Yang
88
95
0
17 Sep 2019
Neural Machine Translation with 4-Bit Precision and Beyond
Neural Machine Translation with 4-Bit Precision and Beyond
Alham Fikri Aji
Kenneth Heafield
MQ
22
7
0
13 Sep 2019
Accelerating Training using Tensor Decomposition
Accelerating Training using Tensor Decomposition
Mostafa Elhoushi
Ye Tian
Zihao Chen
F. Shafiq
Joey Yiwei Li
39
3
0
10 Sep 2019
Gradient Descent with Compressed Iterates
Gradient Descent with Compressed Iterates
Ahmed Khaled
Peter Richtárik
41
22
0
10 Sep 2019
Hierarchical Federated Learning Across Heterogeneous Cellular Networks
Hierarchical Federated Learning Across Heterogeneous Cellular Networks
Mehdi Salehi Heydar Abad
Emre Ozfatura
Deniz Gunduz
Ozgur Ercetin
FedML
143
314
0
05 Sep 2019
Beyond Human-Level Accuracy: Computational Challenges in Deep Learning
Beyond Human-Level Accuracy: Computational Challenges in Deep Learning
Joel Hestness
Newsha Ardalani
G. Diamos
64
68
0
03 Sep 2019
Big Data Analytics for Large Scale Wireless Networks: Challenges and
  Opportunities
Big Data Analytics for Large Scale Wireless Networks: Challenges and Opportunities
Hongning Dai
Raymond Chi-Wing Wong
Hao Wang
Zibin Zheng
A. Vasilakos
AI4CEGNN
63
65
0
02 Sep 2019
Big Data Analytics for Manufacturing Internet of Things: Opportunities,
  Challenges and Enabling Technologies
Big Data Analytics for Manufacturing Internet of Things: Opportunities, Challenges and Enabling Technologies
Hongning Dai
Hao Wang
Guangquan Xu
J. Wan
Muhammad Imran
66
251
0
01 Sep 2019
Recent Advances in Deep Learning for Object Detection
Recent Advances in Deep Learning for Object Detection
Xiongwei Wu
Doyen Sahoo
Guosheng Lin
VLMObjD
131
824
0
10 Aug 2019
Machine Learning at the Network Edge: A Survey
Machine Learning at the Network Edge: A Survey
M. G. Sarwar Murshed
Chris Murphy
Daqing Hou
Nazar Khan
Ganesh Ananthanarayanan
Faraz Hussain
92
391
0
31 Jul 2019
Taming Momentum in a Distributed Asynchronous Environment
Taming Momentum in a Distributed Asynchronous Environment
Ido Hakimi
Saar Barkai
Moshe Gabel
Assaf Schuster
93
23
0
26 Jul 2019
Benchmarking TPU, GPU, and CPU Platforms for Deep Learning
Benchmarking TPU, GPU, and CPU Platforms for Deep Learning
Y. Wang
Gu-Yeon Wei
David Brooks
ELMVLM
97
278
0
24 Jul 2019
Federated Learning over Wireless Fading Channels
Federated Learning over Wireless Fading Channels
M. Amiri
Deniz Gunduz
125
515
0
23 Jul 2019
A Survey on Federated Learning Systems: Vision, Hype and Reality for
  Data Privacy and Protection
A Survey on Federated Learning Systems: Vision, Hype and Reality for Data Privacy and Protection
Yue Liu
Zeyi Wen
Zhaomin Wu
Sixu Hu
Naibo Wang
Yuan N. Li
Xu Liu
Bingsheng He
FedML
130
1,014
0
23 Jul 2019
Decentralized Deep Learning with Arbitrary Communication Compression
Decentralized Deep Learning with Arbitrary Communication Compression
Anastasia Koloskova
Tao R. Lin
Sebastian U. Stich
Martin Jaggi
FedML
92
235
0
22 Jul 2019
Convergence of Edge Computing and Deep Learning: A Comprehensive Survey
Convergence of Edge Computing and Deep Learning: A Comprehensive Survey
Xiaofei Wang
Yiwen Han
Victor C. M. Leung
Dusit Niyato
Xueqiang Yan
Xu Chen
100
1,002
0
19 Jul 2019
Faster Distributed Deep Net Training: Computation and Communication
  Decoupled Stochastic Gradient Descent
Faster Distributed Deep Net Training: Computation and Communication Decoupled Stochastic Gradient Descent
Shuheng Shen
Linli Xu
Jingchang Liu
Xianfeng Liang
Yifei Cheng
ODLFedML
68
24
0
28 Jun 2019
Database Meets Deep Learning: Challenges and Opportunities
Database Meets Deep Learning: Challenges and Opportunities
Wei Wang
Meihui Zhang
Gang Chen
H. V. Jagadish
Beng Chin Ooi
K. Tan
89
148
0
21 Jun 2019
Deep Leakage from Gradients
Deep Leakage from Gradients
Ligeng Zhu
Zhijian Liu
Song Han
FedML
112
2,236
0
21 Jun 2019
Distributed Optimization for Over-Parameterized Learning
Distributed Optimization for Over-Parameterized Learning
Chi Zhang
Qianxiao Li
80
5
0
14 Jun 2019
Associative Convolutional Layers
Associative Convolutional Layers
H. Omidvar
Vahideh Akhlaghi
M. Franceschetti
Rajesh K. Gupta
44
1
0
10 Jun 2019
Making Asynchronous Stochastic Gradient Descent Work for Transformers
Making Asynchronous Stochastic Gradient Descent Work for Transformers
Alham Fikri Aji
Kenneth Heafield
68
13
0
08 Jun 2019
Qsparse-local-SGD: Distributed SGD with Quantization, Sparsification,
  and Local Computations
Qsparse-local-SGD: Distributed SGD with Quantization, Sparsification, and Local Computations
Debraj Basu
Deepesh Data
C. Karakuş
Suhas Diggavi
MQ
74
408
0
06 Jun 2019
PowerSGD: Practical Low-Rank Gradient Compression for Distributed
  Optimization
PowerSGD: Practical Low-Rank Gradient Compression for Distributed Optimization
Thijs Vogels
Sai Praneeth Karimireddy
Martin Jaggi
105
322
0
31 May 2019
On the Convergence of Memory-Based Distributed SGD
On the Convergence of Memory-Based Distributed SGD
Shen-Yi Zhao
Hao Gao
Wu-Jun Li
17
1
0
30 May 2019
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