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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
TopoOpt: Co-optimizing Network Topology and Parallelization Strategy for
  Distributed Training Jobs
TopoOpt: Co-optimizing Network Topology and Parallelization Strategy for Distributed Training Jobs
Weiyang Wang
Moein Khazraee
Zhizhen Zhong
M. Ghobadi
Zhihao Jia
Dheevatsa Mudigere
Ying Zhang
A. Kewitsch
131
93
0
01 Feb 2022
Faster Convergence of Local SGD for Over-Parameterized Models
Faster Convergence of Local SGD for Over-Parameterized Models
Tiancheng Qin
S. Rasoul Etesami
César A. Uribe
FedML
88
6
0
30 Jan 2022
Survey on Federated Learning Threats: concepts, taxonomy on attacks and
  defences, experimental study and challenges
Survey on Federated Learning Threats: concepts, taxonomy on attacks and defences, experimental study and challenges
Nuria Rodríguez-Barroso
Daniel Jiménez López
M. V. Luzón
Francisco Herrera
Eugenio Martínez-Cámara
FedML
85
229
0
20 Jan 2022
DEFER: Distributed Edge Inference for Deep Neural Networks
DEFER: Distributed Edge Inference for Deep Neural Networks
Arjun Parthasarathy
Bhaskar Krishnamachari
39
15
0
18 Jan 2022
Egeria: Efficient DNN Training with Knowledge-Guided Layer Freezing
Egeria: Efficient DNN Training with Knowledge-Guided Layer Freezing
Yiding Wang
D. Sun
Kai Chen
Fan Lai
Mosharaf Chowdhury
97
47
0
17 Jan 2022
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
Nicole Mitchell
Johannes Ballé
Zachary B. Charles
Jakub Konecný
FedML
128
21
0
07 Jan 2022
Automatic Configuration for Optimal Communication Scheduling in DNN
  Training
Automatic Configuration for Optimal Communication Scheduling in DNN Training
Yiqing Ma
Hao Wang
Yiming Zhang
Kai Chen
35
12
0
27 Dec 2021
Sparsified Secure Aggregation for Privacy-Preserving Federated Learning
Sparsified Secure Aggregation for Privacy-Preserving Federated Learning
Irem Ergun
Hasin Us Sami
Başak Güler
FedML
85
26
0
23 Dec 2021
FedLGA: Towards System-Heterogeneity of Federated Learning via Local
  Gradient Approximation
FedLGA: Towards System-Heterogeneity of Federated Learning via Local Gradient Approximation
Xingyu Li
Zhe Qu
Bo Tang
Zhuo Lu
FedML
109
28
0
22 Dec 2021
Efficient Strong Scaling Through Burst Parallel Training
Efficient Strong Scaling Through Burst Parallel Training
S. Park
Joshua Fried
Sunghyun Kim
Mohammad Alizadeh
Adam Belay
GNNLRM
64
11
0
19 Dec 2021
Efficient Differentially Private Secure Aggregation for Federated
  Learning via Hardness of Learning with Errors
Efficient Differentially Private Secure Aggregation for Federated Learning via Hardness of Learning with Errors
Timothy Stevens
Christian Skalka
C. Vincent
J. Ring
Samuel Clark
Joseph P. Near
FedML
75
73
0
13 Dec 2021
Optimal Rate Adaption in Federated Learning with Compressed
  Communications
Optimal Rate Adaption in Federated Learning with Compressed Communications
Laizhong Cui
Xiaoxin Su
Yipeng Zhou
Jiangchuan Liu
FedML
92
43
0
13 Dec 2021
SparseFed: Mitigating Model Poisoning Attacks in Federated Learning with
  Sparsification
SparseFed: Mitigating Model Poisoning Attacks in Federated Learning with Sparsification
Ashwinee Panda
Saeed Mahloujifar
A. Bhagoji
Supriyo Chakraborty
Prateek Mittal
FedMLAAML
76
88
0
12 Dec 2021
Batch Label Inference and Replacement Attacks in Black-Boxed Vertical
  Federated Learning
Batch Label Inference and Replacement Attacks in Black-Boxed Vertical Federated Learning
Yang Liu
Tianyuan Zou
Yan Kang
Wenhan Liu
Yuanqin He
Zhi-qian Yi
Qian Yang
FedMLAAML
140
20
0
10 Dec 2021
PMFL: Partial Meta-Federated Learning for heterogeneous tasks and its
  applications on real-world medical records
PMFL: Partial Meta-Federated Learning for heterogeneous tasks and its applications on real-world medical records
Tianyi Zhang
Shirui Zhang
Ziwei Chen
Dianbo Liu
FedML
78
4
0
10 Dec 2021
FastSGD: A Fast Compressed SGD Framework for Distributed Machine
  Learning
FastSGD: A Fast Compressed SGD Framework for Distributed Machine Learning
Keyu Yang
Lu Chen
Zhihao Zeng
Yunjun Gao
49
9
0
08 Dec 2021
Communication-Efficient Distributed Learning via Sparse and Adaptive
  Stochastic Gradient
Communication-Efficient Distributed Learning via Sparse and Adaptive Stochastic Gradient
Xiaoge Deng
Dongsheng Li
Tao Sun
Xicheng Lu
FedML
60
0
0
08 Dec 2021
Collaborative Learning over Wireless Networks: An Introductory Overview
Collaborative Learning over Wireless Networks: An Introductory Overview
Emre Ozfatura
Deniz Gunduz
H. Vincent Poor
76
12
0
07 Dec 2021
Intrinisic Gradient Compression for Federated Learning
Intrinisic Gradient Compression for Federated Learning
Luke Melas-Kyriazi
Franklyn Wang
FedML
25
3
0
05 Dec 2021
Communication-Efficient Federated Learning via Quantized Compressed
  Sensing
Communication-Efficient Federated Learning via Quantized Compressed Sensing
Yong-Nam Oh
Namyoon Lee
Yo-Seb Jeon
H. Vincent Poor
FedMLMQ
80
36
0
30 Nov 2021
Doing More by Doing Less: How Structured Partial Backpropagation
  Improves Deep Learning Clusters
Doing More by Doing Less: How Structured Partial Backpropagation Improves Deep Learning Clusters
Adarsh Kumar
Kausik Subramanian
Shivaram Venkataraman
Aditya Akella
33
5
0
20 Nov 2021
An Expectation-Maximization Perspective on Federated Learning
An Expectation-Maximization Perspective on Federated Learning
Christos Louizos
M. Reisser
Joseph B. Soriaga
Max Welling
FedML
83
12
0
19 Nov 2021
COMET: A Novel Memory-Efficient Deep Learning Training Framework by
  Using Error-Bounded Lossy Compression
COMET: A Novel Memory-Efficient Deep Learning Training Framework by Using Error-Bounded Lossy Compression
Sian Jin
Chengming Zhang
Xintong Jiang
Yunhe Feng
Hui Guan
Guanpeng Li
Shuaiwen Leon Song
Dingwen Tao
46
25
0
18 Nov 2021
CGX: Adaptive System Support for Communication-Efficient Deep Learning
CGX: Adaptive System Support for Communication-Efficient Deep Learning
I. Markov
Hamidreza Ramezanikebrya
Dan Alistarh
GNN
82
5
0
16 Nov 2021
CoReS: Compatible Representations via Stationarity
CoReS: Compatible Representations via Stationarity
Niccoló Biondi
F. Pernici
Matteo Bruni
A. Bimbo
OOD
63
9
0
15 Nov 2021
Edge-Native Intelligence for 6G Communications Driven by Federated
  Learning: A Survey of Trends and Challenges
Edge-Native Intelligence for 6G Communications Driven by Federated Learning: A Survey of Trends and Challenges
Mohammad M. Al-Quraan
Lina S. Mohjazi
Lina Bariah
A. Centeno
A. Zoha
Sami Muhaidat
Mérouane Debbah
Muhammad Ali Imran
102
67
0
14 Nov 2021
SEOFP-NET: Compression and Acceleration of Deep Neural Networks for
  Speech Enhancement Using Sign-Exponent-Only Floating-Points
SEOFP-NET: Compression and Acceleration of Deep Neural Networks for Speech Enhancement Using Sign-Exponent-Only Floating-Points
Yu-Chen Lin
Cheng Yu
Y. Hsu
Szu-Wei Fu
Yu Tsao
Tei-Wei Kuo
31
6
0
08 Nov 2021
Finite-Time Consensus Learning for Decentralized Optimization with
  Nonlinear Gossiping
Finite-Time Consensus Learning for Decentralized Optimization with Nonlinear Gossiping
Junya Chen
Sijia Wang
Lawrence Carin
Chenyang Tao
39
3
0
04 Nov 2021
Large-Scale Deep Learning Optimizations: A Comprehensive Survey
Large-Scale Deep Learning Optimizations: A Comprehensive Survey
Xiaoxin He
Fuzhao Xue
Xiaozhe Ren
Yang You
90
15
0
01 Nov 2021
Gradient Inversion with Generative Image Prior
Gradient Inversion with Generative Image Prior
Jinwoo Jeon
Jaechang Kim
Kangwook Lee
Sewoong Oh
Jungseul Ok
77
158
0
28 Oct 2021
Federated Learning over Wireless IoT Networks with Optimized
  Communication and Resources
Federated Learning over Wireless IoT Networks with Optimized Communication and Resources
Student Member Ieee Hao Chen
Shaocheng Huang
Deyou Zhang
Ming Xiao
Fellow Ieee Mikael Skoglund
L. F. I. H. Vincent Poor
93
96
0
22 Oct 2021
BEV-SGD: Best Effort Voting SGD for Analog Aggregation Based Federated
  Learning against Byzantine Attackers
BEV-SGD: Best Effort Voting SGD for Analog Aggregation Based Federated Learning against Byzantine Attackers
Xin-Yue Fan
Yue Wang
Yan Huo
Zhi Tian
FedML
85
24
0
18 Oct 2021
EmbRace: Accelerating Sparse Communication for Distributed Training of
  NLP Neural Networks
EmbRace: Accelerating Sparse Communication for Distributed Training of NLP Neural Networks
Shengwei Li
Zhiquan Lai
Dongsheng Li
Yiming Zhang
Xiangyu Ye
Yabo Duan
FedML
63
3
0
18 Oct 2021
Federated learning and next generation wireless communications: A survey
  on bidirectional relationship
Federated learning and next generation wireless communications: A survey on bidirectional relationship
Debaditya Shome
Omer Waqar
Wali Ullah Khan
88
32
0
14 Oct 2021
ProgFed: Effective, Communication, and Computation Efficient Federated
  Learning by Progressive Training
ProgFed: Effective, Communication, and Computation Efficient Federated Learning by Progressive Training
Hui-Po Wang
Sebastian U. Stich
Yang He
Mario Fritz
FedMLAI4CE
73
50
0
11 Oct 2021
An Empirical Study on Compressed Decentralized Stochastic Gradient
  Algorithms with Overparameterized Models
An Empirical Study on Compressed Decentralized Stochastic Gradient Algorithms with Overparameterized Models
A. Rao
Hoi-To Wai
28
0
0
09 Oct 2021
Distributed Methods with Compressed Communication for Solving
  Variational Inequalities, with Theoretical Guarantees
Distributed Methods with Compressed Communication for Solving Variational Inequalities, with Theoretical Guarantees
Aleksandr Beznosikov
Peter Richtárik
Michael Diskin
Max Ryabinin
Alexander Gasnikov
FedML
105
22
0
07 Oct 2021
S2 Reducer: High-Performance Sparse Communication to Accelerate
  Distributed Deep Learning
S2 Reducer: High-Performance Sparse Communication to Accelerate Distributed Deep Learning
Ke-shi Ge
Yongquan Fu
Zhiquan Lai
Xiaoge Deng
Dongsheng Li
48
2
0
05 Oct 2021
Solon: Communication-efficient Byzantine-resilient Distributed Training
  via Redundant Gradients
Solon: Communication-efficient Byzantine-resilient Distributed Training via Redundant Gradients
Lingjiao Chen
Leshang Chen
Hongyi Wang
S. Davidson
Yan Sun
FedML
66
1
0
04 Oct 2021
Algorithm Fairness in AI for Medicine and Healthcare
Algorithm Fairness in AI for Medicine and Healthcare
Richard J. Chen
Tiffany Y. Chen
Jana Lipkova
Judy J. Wang
Drew F. K. Williamson
Ming Y. Lu
S. Sahai
Faisal Mahmood
FaML
150
47
0
01 Oct 2021
Unbiased Single-scale and Multi-scale Quantizers for Distributed
  Optimization
Unbiased Single-scale and Multi-scale Quantizers for Distributed Optimization
S. Vineeth
MQ
35
0
0
26 Sep 2021
Toward Communication Efficient Adaptive Gradient Method
Toward Communication Efficient Adaptive Gradient Method
Xiangyi Chen
Xiaoyun Li
P. Li
FedML
80
42
0
10 Sep 2021
On the Convergence of Decentralized Adaptive Gradient Methods
On the Convergence of Decentralized Adaptive Gradient Methods
Xiangyi Chen
Belhal Karimi
Weijie Zhao
Ping Li
85
21
0
07 Sep 2021
FLASHE: Additively Symmetric Homomorphic Encryption for Cross-Silo
  Federated Learning
FLASHE: Additively Symmetric Homomorphic Encryption for Cross-Silo Federated Learning
Zhifeng Jiang
Wen Wang
Yang Liu
FedML
96
50
0
02 Sep 2021
Efficient Visual Recognition with Deep Neural Networks: A Survey on
  Recent Advances and New Directions
Efficient Visual Recognition with Deep Neural Networks: A Survey on Recent Advances and New Directions
Yang Wu
Dingheng Wang
Xiaotong Lu
Fan Yang
Guoqi Li
W. Dong
Jianbo Shi
104
18
0
30 Aug 2021
Rate distortion comparison of a few gradient quantizers
Rate distortion comparison of a few gradient quantizers
Tharindu B. Adikari
MQ
20
0
0
23 Aug 2021
FedSkel: Efficient Federated Learning on Heterogeneous Systems with
  Skeleton Gradients Update
FedSkel: Efficient Federated Learning on Heterogeneous Systems with Skeleton Gradients Update
Junyu Luo
Jianlei Yang
Xucheng Ye
Xin Guo
Weisheng Zhao
FedML
59
14
0
20 Aug 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
118
49
0
19 Aug 2021
Compressing gradients by exploiting temporal correlation in momentum-SGD
Compressing gradients by exploiting temporal correlation in momentum-SGD
Tharindu B. Adikari
S. Draper
20
0
0
17 Aug 2021
FedPara: Low-Rank Hadamard Product for Communication-Efficient Federated
  Learning
FedPara: Low-Rank Hadamard Product for Communication-Efficient Federated Learning
Nam Hyeon-Woo
Moon Ye-Bin
Tae-Hyun Oh
FedML
132
125
0
13 Aug 2021
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