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Communication-Efficient Learning of Deep Networks from Decentralized Data

17 February 2016

Blaise Agüera y Arcas

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

37 / 5,637 papers shown

Title
DÏoT: A Federated Self-learning Anomaly Detection System for IoT T. D. Nguyen Samuel Marchal Markus Miettinen Hossein Fereidooni Nadarajah Asokan A. Sadeghi 207 497 0 20 Apr 2018
Adaptive Federated Learning in Resource Constrained Edge Computing Systems Shiqiang Wang Tiffany Tuor Theodoros Salonidis K. Leung C. Makaya T. He Kevin S. Chan 280 1,729 0 14 Apr 2018
Large scale distributed neural network training through online distillation Rohan Anil Gabriel Pereyra Alexandre Passos Róbert Ormándi George E. Dahl Geoffrey E. Hinton FedML 341 409 0 09 Apr 2018
Deep Learning in Mobile and Wireless Networking: A Survey Chaoyun Zhang P. Patras Hamed Haddadi 138 1,320 0 12 Mar 2018
Byzantine-Robust Distributed Learning: Towards Optimal Statistical Rates Dong Yin Yudong Chen Kannan Ramchandran Peter L. Bartlett OOD FedML 197 1,540 0 05 Mar 2018
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 86 198 0 03 Mar 2018
Generalized Byzantine-tolerant SGD Cong Xie Oluwasanmi Koyejo Indranil Gupta AAML 84 260 0 27 Feb 2018
Geometric Lower Bounds for Distributed Parameter Estimation under Communication Constraints Yanjun Han Ayfer Özgür Tsachy Weissman 118 91 0 23 Feb 2018
Federated Meta-Learning with Fast Convergence and Efficient Communication Fei Chen Mi Luo Zhenhua Dong Zhenguo Li Xiuqiang He FedML 83 398 0 22 Feb 2018
3LC: Lightweight and Effective Traffic Compression for Distributed Machine Learning Hyeontaek Lim D. Andersen M. Kaminsky 139 70 0 21 Feb 2018
A Scalable Near-Memory Architecture for Training Deep Neural Networks on Large In-Memory Datasets Fabian Schuiki Michael Schaffner Frank K. Gürkaynak Luca Benini 66 70 0 19 Feb 2018
Cloud No Longer a Silver Bullet, Edge to the Rescue Yuhao Zhu Gu-Yeon Wei David Brooks 23 4 0 15 Feb 2018
RoboChain: A Secure Data-Sharing Framework for Human-Robot Interaction Eduardo Castelló Ferrer Ognjen Rudovic Thomas Hardjono Alex Pentland 58 62 0 13 Feb 2018
Distributed One-class Learning Ali Shahin Shamsabadi Hamed Haddadi Andrea Cavallaro PICV 48 10 0 10 Feb 2018
MXNET-MPI: Embedding MPI parallelism in Parameter Server Task Model for scaling Deep Learning Amith R. Mamidala Georgios Kollias C. Ward F. Artico 80 20 0 11 Jan 2018
Differentially Private Federated Learning: A Client Level Perspective Robin C. Geyer T. Klein Moin Nabi FedML 198 1,309 0 20 Dec 2017
A Berkeley View of Systems Challenges for AI Ion Stoica Basel Alomair Raluca A. Popa D. Patterson Michael W. Mahoney ... Joseph E. Gonzalez Ken Goldberg A. Ghodsi David Culler Pieter Abbeel 87 201 0 15 Dec 2017
Deep Gradient Compression: Reducing the Communication Bandwidth for Distributed Training Chengyue Wu Song Han Huizi Mao Yu Wang W. Dally 284 1,415 0 05 Dec 2017
Together or Alone: The Price of Privacy in Collaborative Learning Balázs Pejó Qiang Tang G. Biczók FedML 122 16 0 01 Dec 2017
Private federated learning on vertically partitioned data via entity resolution and additively homomorphic encryption Stephen Hardy Wilko Henecka Hamish Ivey-Law Richard Nock Giorgio Patrini Guillaume Smith Brian Thorne FedML 84 539 0 29 Nov 2017
Random gradient extrapolation for distributed and stochastic optimization Guanghui Lan Yi Zhou 90 52 0 15 Nov 2017
GIANT: Globally Improved Approximate Newton Method for Distributed Optimization Shusen Wang Farbod Roosta-Khorasani Peng Xu Michael W. Mahoney 137 130 0 11 Sep 2017
Stochastic, Distributed and Federated Optimization for Machine Learning Jakub Konecný FedML 83 38 0 04 Jul 2017
Collaborative Deep Learning in Fixed Topology Networks Zhanhong Jiang Aditya Balu Chinmay Hegde Soumik Sarkar FedML 84 181 0 23 Jun 2017
Stochastic Training of Neural Networks via Successive Convex Approximations Simone Scardapane Paolo Di Lorenzo 55 9 0 15 Jun 2017
Federated Multi-Task Learning Virginia Smith Chao-Kai Chiang Maziar Sanjabi Ameet Talwalkar FedML 177 1,825 0 30 May 2017
Continual Learning in Generative Adversarial Nets Ari Seff Alex Beatson Daniel Suo Han Liu GAN 82 133 0 23 May 2017
EE-Grad: Exploration and Exploitation for Cost-Efficient Mini-Batch SGD Mehmet A. Donmez Maxim Raginsky A. Singer FedML 16 0 0 19 May 2017
Privacy-Preserving Personal Model Training S. S. Rodríguez Liang Wang Jianxin R. Zhao Richard Mortier Hamed Haddadi 61 23 0 01 Mar 2017
Practical Secure Aggregation for Federated Learning on User-Held Data Keith Bonawitz Vladimir Ivanov Ben Kreuter Antonio Marcedone H. B. McMahan Sarvar Patel Daniel Ramage Aaron Segal Karn Seth FedML 90 508 0 14 Nov 2016
Distributed Mean Estimation with Limited Communication A. Suresh Felix X. Yu Sanjiv Kumar H. B. McMahan FedML 169 368 0 02 Nov 2016
Federated Learning: Strategies for Improving Communication Efficiency Jakub Konecný H. B. McMahan Felix X. Yu Peter Richtárik A. Suresh Dave Bacon FedML 369 4,681 0 18 Oct 2016
Decentralized Collaborative Learning of Personalized Models over Networks Paul Vanhaesebrouck A. Bellet Marc Tommasi FedML 89 231 0 17 Oct 2016
Federated Optimization: Distributed Machine Learning for On-Device Intelligence Jakub Konecný H. B. McMahan Daniel Ramage Peter Richtárik FedML 196 1,916 0 08 Oct 2016
Towards Geo-Distributed Machine Learning Ignacio Cano Markus Weimer D. Mahajan Carlo Curino Giovanni Matteo Fumarola 71 56 0 30 Mar 2016
Scalable and Sustainable Deep Learning via Randomized Hashing Ryan Spring Anshumali Shrivastava 108 133 0 26 Feb 2016
Distributed Bayesian Learning with Stochastic Natural-gradient Expectation Propagation and the Posterior Server Leonard Hasenclever Stefan Webb Thibaut Lienart Sebastian J. Vollmer Balaji Lakshminarayanan Charles Blundell Yee Whye Teh BDL 203 70 0 31 Dec 2015