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Federated Learning: Strategies for Improving Communication Efficiency

Federated Learning: Strategies for Improving Communication Efficiency

18 October 2016
Jakub Konecný
H. B. McMahan
Felix X. Yu
Peter Richtárik
A. Suresh
Dave Bacon
    FedML
ArXivPDFHTML

Papers citing "Federated Learning: Strategies for Improving Communication Efficiency"

48 / 1,848 papers shown
Title
Hydra: A Peer to Peer Distributed Training & Data Collection Framework
Hydra: A Peer to Peer Distributed Training & Data Collection Framework
Vaibhav Mathur
K. Chahal
OffRL
11
2
0
24 Nov 2018
WEST: Word Encoded Sequence Transducers
WEST: Word Encoded Sequence Transducers
Ehsan Variani
A. Suresh
M. Weintraub
17
9
0
20 Nov 2018
MD-GAN: Multi-Discriminator Generative Adversarial Networks for
  Distributed Datasets
MD-GAN: Multi-Discriminator Generative Adversarial Networks for Distributed Datasets
Corentin Hardy
Erwan Le Merrer
B. Sericola
GAN
27
181
0
09 Nov 2018
A Hitchhiker's Guide On Distributed Training of Deep Neural Networks
A Hitchhiker's Guide On Distributed Training of Deep Neural Networks
K. Chahal
Manraj Singh Grover
Kuntal Dey
3DH
OOD
4
53
0
28 Oct 2018
K for the Price of 1: Parameter-efficient Multi-task and Transfer
  Learning
K for the Price of 1: Parameter-efficient Multi-task and Transfer Learning
Pramod Kaushik Mudrakarta
Mark Sandler
A. Zhmoginov
Andrew G. Howard
14
67
0
25 Oct 2018
Computation Scheduling for Distributed Machine Learning with Straggling
  Workers
Computation Scheduling for Distributed Machine Learning with Straggling Workers
Mohammad Mohammadi Amiri
Deniz Gunduz
FedML
11
2
0
23 Oct 2018
Federated Learning for Keyword Spotting
Federated Learning for Keyword Spotting
David Leroy
A. Coucke
Thibaut Lavril
Thibault Gisselbrecht
Joseph Dureau
FedML
13
282
0
09 Oct 2018
Generalizing the theory of cooperative inference
Generalizing the theory of cooperative inference
Pei Wang
P. Paranamana
Patrick Shafto
FedML
13
14
0
04 Oct 2018
Universal Multi-Party Poisoning Attacks
Universal Multi-Party Poisoning Attacks
Saeed Mahloujifar
Mohammad Mahmoody
Ameer Mohammed
AAML
12
43
0
10 Sep 2018
Cooperative SGD: A unified Framework for the Design and Analysis of
  Communication-Efficient SGD Algorithms
Cooperative SGD: A unified Framework for the Design and Analysis of Communication-Efficient SGD Algorithms
Jianyu Wang
Gauri Joshi
30
348
0
22 Aug 2018
Don't Use Large Mini-Batches, Use Local SGD
Don't Use Large Mini-Batches, Use Local SGD
Tao R. Lin
Sebastian U. Stich
Kumar Kshitij Patel
Martin Jaggi
57
429
0
22 Aug 2018
A Survey on Methods and Theories of Quantized Neural Networks
A Survey on Methods and Theories of Quantized Neural Networks
Yunhui Guo
MQ
29
230
0
13 Aug 2018
COLA: Decentralized Linear Learning
COLA: Decentralized Linear Learning
Lie He
An Bian
Martin Jaggi
14
117
0
13 Aug 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'
19
21
0
05 Jul 2018
How To Backdoor Federated Learning
How To Backdoor Federated Learning
Eugene Bagdasaryan
Andreas Veit
Yiqing Hua
D. Estrin
Vitaly Shmatikov
SILM
FedML
13
1,873
0
02 Jul 2018
ATOMO: Communication-efficient Learning via Atomic Sparsification
ATOMO: Communication-efficient Learning via Atomic Sparsification
Hongyi Wang
Scott Sievert
Zachary B. Charles
Shengchao Liu
S. Wright
Dimitris Papailiopoulos
18
350
0
11 Jun 2018
Federated Learning with Non-IID Data
Federated Learning with Non-IID Data
Yue Zhao
Meng Li
Liangzhen Lai
Naveen Suda
Damon Civin
Vikas Chandra
FedML
14
2,513
0
02 Jun 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
8
485
0
27 May 2018
Zeno: Distributed Stochastic Gradient Descent with Suspicion-based
  Fault-tolerance
Zeno: Distributed Stochastic Gradient Descent with Suspicion-based Fault-tolerance
Cong Xie
Oluwasanmi Koyejo
Indranil Gupta
FedML
8
46
0
25 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
13
211
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
354
37
0
15 May 2018
PRADA: Protecting against DNN Model Stealing Attacks
PRADA: Protecting against DNN Model Stealing Attacks
Mika Juuti
S. Szyller
Samuel Marchal
Nadarajah Asokan
SILM
AAML
28
439
0
07 May 2018
Securing Distributed Gradient Descent in High Dimensional Statistical
  Learning
Securing Distributed Gradient Descent in High Dimensional Statistical Learning
Lili Su
Jiaming Xu
FedML
137
35
0
26 Apr 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
17
1,369
0
23 Apr 2018
Value-aware Quantization for Training and Inference of Neural Networks
Value-aware Quantization for Training and Inference of Neural Networks
Eunhyeok Park
S. Yoo
Peter Vajda
MQ
6
158
0
20 Apr 2018
DÏoT: A Federated Self-learning Anomaly Detection System for IoT
DÏoT: A Federated Self-learning Anomaly Detection System for IoT
T. D. Nguyen
Samuel Marchal
Markus Miettinen
Hossein Fereidooni
Nadarajah Asokan
A. Sadeghi
62
488
0
20 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
1,687
0
14 Apr 2018
DRACO: Byzantine-resilient Distributed Training via Redundant Gradients
DRACO: Byzantine-resilient Distributed Training via Redundant Gradients
Lingjiao Chen
Hongyi Wang
Zachary B. Charles
Dimitris Papailiopoulos
11
243
0
27 Mar 2018
Byzantine Stochastic Gradient Descent
Byzantine Stochastic Gradient Descent
Dan Alistarh
Zeyuan Allen-Zhu
J. Li
FedML
16
296
0
23 Mar 2018
Entity Resolution and Federated Learning get a Federated Resolution
Entity Resolution and Federated Learning get a Federated Resolution
Richard Nock
Stephen Hardy
Wilko Henecka
Hamish Ivey-Law
Giorgio Patrini
Guillaume Smith
Brian Thorne
FedML
13
87
0
11 Mar 2018
Byzantine-Robust Distributed Learning: Towards Optimal Statistical Rates
Byzantine-Robust Distributed Learning: Towards Optimal Statistical Rates
Dong Yin
Yudong Chen
Kannan Ramchandran
Peter L. Bartlett
OOD
FedML
11
1,461
0
05 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
22
193
0
03 Mar 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
13
70
0
21 Feb 2018
Sometimes You Want to Go Where Everybody Knows your Name
Sometimes You Want to Go Where Everybody Knows your Name
Reuben Brasher
Nat Roth
Justin Wagle
25
0
0
30 Jan 2018
Differentially Private Distributed Learning for Language Modeling Tasks
Differentially Private Distributed Learning for Language Modeling Tasks
Vadim Popov
Mikhail Kudinov
Irina Piontkovskaya
Petr Vytovtov
A. Nevidomsky
FedML
18
3
0
20 Dec 2017
Deep Gradient Compression: Reducing the Communication Bandwidth for
  Distributed Training
Deep Gradient Compression: Reducing the Communication Bandwidth for Distributed Training
Yujun Lin
Song Han
Huizi Mao
Yu Wang
W. Dally
39
1,385
0
05 Dec 2017
Learning Discrete Distributions from Untrusted Batches
Learning Discrete Distributions from Untrusted Batches
Mingda Qiao
Gregory Valiant
FedML
17
34
0
22 Nov 2017
Unsupervised Machine Learning for Networking: Techniques, Applications
  and Research Challenges
Unsupervised Machine Learning for Networking: Techniques, Applications and Research Challenges
Muhammad Usama
Junaid Qadir
Aunn Raza
Hunain Arif
K. Yau
Y. Elkhatib
Amir Hussain
Ala I. Al-Fuqaha
SSL
25
315
0
19 Sep 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
30
127
0
11 Sep 2017
Stochastic, Distributed and Federated Optimization for Machine Learning
Stochastic, Distributed and Federated Optimization for Machine Learning
Jakub Konecný
FedML
21
38
0
04 Jul 2017
Federated Multi-Task Learning
Federated Multi-Task Learning
Virginia Smith
Chao-Kai Chiang
Maziar Sanjabi
Ameet Talwalkar
FedML
15
1,776
0
30 May 2017
A Hybrid Deep Learning Architecture for Privacy-Preserving Mobile
  Analytics
A Hybrid Deep Learning Architecture for Privacy-Preserving Mobile Analytics
Seyed Ali Osia
Ali Shahin Shamsabadi
Sina Sajadmanesh
A. Taheri
Kleomenis Katevas
Hamid R. Rabiee
Nicholas D. Lane
Hamed Haddadi
9
234
0
08 Mar 2017
Distributed deep learning on edge-devices: feasibility via adaptive
  compression
Distributed deep learning on edge-devices: feasibility via adaptive compression
Corentin Hardy
Erwan Le Merrer
B. Sericola
14
64
0
15 Feb 2017
Randomized Distributed Mean Estimation: Accuracy vs Communication
Randomized Distributed Mean Estimation: Accuracy vs Communication
Jakub Konecný
Peter Richtárik
FedML
17
101
0
22 Nov 2016
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
Towards Geo-Distributed Machine Learning
Towards Geo-Distributed Machine Learning
Ignacio Cano
Markus Weimer
D. Mahajan
Carlo Curino
Giovanni Matteo Fumarola
11
56
0
30 Mar 2016
Communication-Efficient Learning of Deep Networks from Decentralized
  Data
Communication-Efficient Learning of Deep Networks from Decentralized Data
H. B. McMahan
Eider Moore
Daniel Ramage
S. Hampson
Blaise Agüera y Arcas
FedML
24
16,996
0
17 Feb 2016
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