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Communication-Efficient Learning of Deep Networks from Decentralized
  Data

Communication-Efficient Learning of Deep Networks from Decentralized Data

17 February 2016
H. B. McMahan
Eider Moore
Daniel Ramage
S. Hampson
Blaise Agüera y Arcas
    FedML
ArXivPDFHTML

Papers citing "Communication-Efficient Learning of Deep Networks from Decentralized Data"

41 / 2,541 papers shown
Title
Mitigating Sybils in Federated Learning Poisoning
Mitigating Sybils in Federated Learning Poisoning
Clement Fung
Chris J. M. Yoon
Ivan Beschastnikh
AAML
15
497
0
14 Aug 2018
COLA: Decentralized Linear Learning
COLA: Decentralized Linear Learning
Lie He
An Bian
Martin Jaggi
24
117
0
13 Aug 2018
Quantized Densely Connected U-Nets for Efficient Landmark Localization
Quantized Densely Connected U-Nets for Efficient Landmark Localization
Zhiqiang Tang
Xi Peng
Shijie Geng
Lingfei Wu
Shaoting Zhang
Dimitris N. Metaxas
3DV
19
143
0
07 Aug 2018
Differentially-Private "Draw and Discard" Machine Learning
Differentially-Private "Draw and Discard" Machine Learning
Vasyl Pihur
Aleksandra Korolova
Frederick Liu
Subhash Sankuratripati
M. Yung
Dachuan Huang
Ruogu Zeng
FedML
33
39
0
11 Jul 2018
Efficient Decentralized Deep Learning by Dynamic Model Averaging
Efficient Decentralized Deep Learning by Dynamic Model Averaging
Michael Kamp
Linara Adilova
Joachim Sicking
Fabian Hüger
Peter Schlicht
Tim Wirtz
Stefan Wrobel
32
129
0
09 Jul 2018
Blockchain as a Service: A Decentralized and Secure Computing Paradigm
Blockchain as a Service: A Decentralized and Secure Computing Paradigm
G. Mendis
Yifu Wu
Jin Wei
Moein Sabounchi
Rigoberto Roche'
29
21
0
05 Jul 2018
Confidential Inference via Ternary Model Partitioning
Confidential Inference via Ternary Model Partitioning
Zhongshu Gu
Heqing Huang
Jialong Zhang
D. Su
Hani Jamjoom
Ankita Lamba
Dimitrios E. Pendarakis
Ian Molloy
21
53
0
03 Jul 2018
Compact and Computationally Efficient Representation of Deep Neural
  Networks
Compact and Computationally Efficient Representation of Deep Neural Networks
Simon Wiedemann
K. Müller
Wojciech Samek
MQ
42
67
0
27 May 2018
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
Graph Oracle Models, Lower Bounds, and Gaps for Parallel Stochastic
  Optimization
Graph Oracle Models, Lower Bounds, and Gaps for Parallel Stochastic Optimization
Blake E. Woodworth
Jialei Wang
Adam D. Smith
H. B. McMahan
Nathan Srebro
14
123
0
25 May 2018
LAG: Lazily Aggregated Gradient for Communication-Efficient Distributed
  Learning
LAG: Lazily Aggregated Gradient for Communication-Efficient Distributed Learning
Tianyi Chen
G. Giannakis
Tao Sun
W. Yin
34
297
0
25 May 2018
Local SGD Converges Fast and Communicates Little
Local SGD Converges Fast and Communicates Little
Sebastian U. Stich
FedML
85
1,047
0
24 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
Gradient-Leaks: Understanding and Controlling Deanonymization in
  Federated Learning
Gradient-Leaks: Understanding and Controlling Deanonymization in Federated Learning
Tribhuvanesh Orekondy
Seong Joon Oh
Yang Zhang
Bernt Schiele
Mario Fritz
PICV
FedML
359
37
0
15 May 2018
Exploiting Unintended Feature Leakage in Collaborative Learning
Exploiting Unintended Feature Leakage in Collaborative Learning
Luca Melis
Congzheng Song
Emiliano De Cristofaro
Vitaly Shmatikov
FedML
93
1,455
0
10 May 2018
Client Selection for Federated Learning with Heterogeneous Resources in
  Mobile Edge
Client Selection for Federated Learning with Heterogeneous Resources in Mobile Edge
Takayuki Nishio
Ryo Yonetani
FedML
49
1,376
0
23 Apr 2018
Adaptive Federated Learning in Resource Constrained Edge Computing
  Systems
Adaptive Federated Learning in Resource Constrained Edge Computing Systems
Shiqiang Wang
Tiffany Tuor
Theodoros Salonidis
K. Leung
C. Makaya
T. He
Kevin S. Chan
144
1,688
0
14 Apr 2018
Deep Learning in Mobile and Wireless Networking: A Survey
Deep Learning in Mobile and Wireless Networking: A Survey
Chaoyun Zhang
P. Patras
Hamed Haddadi
47
1,306
0
12 Mar 2018
Slow and Stale Gradients Can Win the Race: Error-Runtime Trade-offs in
  Distributed SGD
Slow and Stale Gradients Can Win the Race: Error-Runtime Trade-offs in Distributed SGD
Sanghamitra Dutta
Gauri Joshi
Soumyadip Ghosh
Parijat Dube
P. Nagpurkar
31
194
0
03 Mar 2018
Generalized Byzantine-tolerant SGD
Generalized Byzantine-tolerant SGD
Cong Xie
Oluwasanmi Koyejo
Indranil Gupta
AAML
19
254
0
27 Feb 2018
Geometric Lower Bounds for Distributed Parameter Estimation under
  Communication Constraints
Geometric Lower Bounds for Distributed Parameter Estimation under Communication Constraints
Yanjun Han
Ayfer Özgür
Tsachy Weissman
40
90
0
23 Feb 2018
Federated Meta-Learning with Fast Convergence and Efficient
  Communication
Federated Meta-Learning with Fast Convergence and Efficient Communication
Fei Chen
Mi Luo
Zhenhua Dong
Zhenguo Li
Xiuqiang He
FedML
34
388
0
22 Feb 2018
3LC: Lightweight and Effective Traffic Compression for Distributed
  Machine Learning
3LC: Lightweight and Effective Traffic Compression for Distributed Machine Learning
Hyeontaek Lim
D. Andersen
M. Kaminsky
21
70
0
21 Feb 2018
A Scalable Near-Memory Architecture for Training Deep Neural Networks on
  Large In-Memory Datasets
A Scalable Near-Memory Architecture for Training Deep Neural Networks on Large In-Memory Datasets
Fabian Schuiki
Michael Schaffner
Frank K. Gürkaynak
Luca Benini
31
70
0
19 Feb 2018
RoboChain: A Secure Data-Sharing Framework for Human-Robot Interaction
RoboChain: A Secure Data-Sharing Framework for Human-Robot Interaction
Eduardo Castelló Ferrer
Ognjen Rudovic
Thomas Hardjono
Alex Pentland
29
62
0
13 Feb 2018
Distributed One-class Learning
Distributed One-class Learning
Ali Shahin Shamsabadi
Hamed Haddadi
Andrea Cavallaro
PICV
16
10
0
10 Feb 2018
Differentially Private Federated Learning: A Client Level Perspective
Differentially Private Federated Learning: A Client Level Perspective
Robin C. Geyer
T. Klein
Moin Nabi
FedML
57
1,280
0
20 Dec 2017
A Berkeley View of Systems Challenges for AI
A Berkeley View of Systems Challenges for AI
Ion Stoica
D. Song
Raluca A. Popa
D. Patterson
Michael W. Mahoney
...
Joseph E. Gonzalez
Ken Goldberg
A. Ghodsi
David Culler
Pieter Abbeel
30
199
0
15 Dec 2017
Deep Gradient Compression: Reducing the Communication Bandwidth for
  Distributed Training
Deep Gradient Compression: Reducing the Communication Bandwidth for Distributed Training
Chengyue Wu
Song Han
Huizi Mao
Yu Wang
W. Dally
59
1,388
0
05 Dec 2017
Together or Alone: The Price of Privacy in Collaborative Learning
Together or Alone: The Price of Privacy in Collaborative Learning
Balázs Pejó
Qiang Tang
G. Biczók
FedML
24
16
0
01 Dec 2017
GIANT: Globally Improved Approximate Newton Method for Distributed
  Optimization
GIANT: Globally Improved Approximate Newton Method for Distributed Optimization
Shusen Wang
Farbod Roosta-Khorasani
Peng Xu
Michael W. Mahoney
36
127
0
11 Sep 2017
Collaborative Deep Learning in Fixed Topology Networks
Collaborative Deep Learning in Fixed Topology Networks
Zhanhong Jiang
Aditya Balu
C. Hegde
S. Sarkar
FedML
32
179
0
23 Jun 2017
Stochastic Training of Neural Networks via Successive Convex
  Approximations
Stochastic Training of Neural Networks via Successive Convex Approximations
Simone Scardapane
P. Di Lorenzo
24
9
0
15 Jun 2017
Federated Multi-Task Learning
Federated Multi-Task Learning
Virginia Smith
Chao-Kai Chiang
Maziar Sanjabi
Ameet Talwalkar
FedML
17
1,782
0
30 May 2017
Continual Learning in Generative Adversarial Nets
Continual Learning in Generative Adversarial Nets
Ari Seff
Alex Beatson
Daniel Suo
Han Liu
GAN
19
132
0
23 May 2017
Distributed Mean Estimation with Limited Communication
Distributed Mean Estimation with Limited Communication
A. Suresh
Felix X. Yu
Sanjiv Kumar
H. B. McMahan
FedML
33
361
0
02 Nov 2016
Federated Learning: Strategies for Improving Communication Efficiency
Federated Learning: Strategies for Improving Communication Efficiency
Jakub Konecný
H. B. McMahan
Felix X. Yu
Peter Richtárik
A. Suresh
Dave Bacon
FedML
93
4,598
0
18 Oct 2016
Federated Optimization: Distributed Machine Learning for On-Device
  Intelligence
Federated Optimization: Distributed Machine Learning for On-Device Intelligence
Jakub Konecný
H. B. McMahan
Daniel Ramage
Peter Richtárik
FedML
69
1,877
0
08 Oct 2016
Towards Geo-Distributed Machine Learning
Towards Geo-Distributed Machine Learning
Ignacio Cano
Markus Weimer
D. Mahajan
Carlo Curino
Giovanni Matteo Fumarola
25
56
0
30 Mar 2016
Scalable and Sustainable Deep Learning via Randomized Hashing
Scalable and Sustainable Deep Learning via Randomized Hashing
Ryan Spring
Anshumali Shrivastava
29
132
0
26 Feb 2016
The Loss Surfaces of Multilayer Networks
The Loss Surfaces of Multilayer Networks
A. Choromańska
Mikael Henaff
Michaël Mathieu
Gerard Ben Arous
Yann LeCun
ODL
186
1,186
0
30 Nov 2014
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