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Communication-Efficient Learning of Deep Networks from Decentralized Data

17 February 2016

Blaise Agüera y Arcas

FedML

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

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Title
Analyzing Federated Learning through an Adversarial Lens A. Bhagoji Supriyo Chakraborty Prateek Mittal S. Calo FedML 321 1,065 0 29 Nov 2018
Communication-Efficient On-Device Machine Learning: Federated Distillation and Augmentation under Non-IID Private Data Eunjeong Jeong Seungeun Oh Hyesung Kim Jihong Park M. Bennis Seong-Lyun Kim FedML 97 604 0 28 Nov 2018
FADL:Federated-Autonomous Deep Learning for Distributed Electronic Health Record Dianbo Liu Timothy A. Miller R. Sayeed K. Mandl FedML OOD 88 62 0 28 Nov 2018
Partitioned Variational Inference: A unified framework encompassing federated and continual learning T. Bui Cuong V Nguyen S. Swaroop Richard Turner FedML 95 56 0 27 Nov 2018
Stochastic Gradient Push for Distributed Deep Learning Mahmoud Assran Nicolas Loizou Nicolas Ballas Michael G. Rabbat 125 347 0 27 Nov 2018
A Survey of Mobile Computing for the Visually Impaired Martin Weiss Margaux Luck Roger Girgis C. Pal Joseph Paul Cohen 59 10 0 25 Nov 2018
An overview of deep learning in medical imaging focusing on MRI A. Lundervold A. Lundervold OOD 112 1,654 0 25 Nov 2018
Biscotti: A Ledger for Private and Secure Peer-to-Peer Machine Learning Muhammad Shayan Clement Fung Chris J. M. Yoon Ivan Beschastnikh FedML 102 82 0 24 Nov 2018
Dancing in the Dark: Private Multi-Party Machine Learning in an Untrusted Setting Clement Fung Jamie Koerner Stewart Grant Ivan Beschastnikh OOD FedML 60 12 0 23 Nov 2018
Federated Learning for Mobile Keyboard Prediction Andrew Straiton Hard Kanishka Rao Zhifeng Lin Swaroop Indra Ramaswamy Youjie Li S. Augenstein Alex Schwing M. Annavaram A. Avestimehr FedML 157 1,558 0 08 Nov 2018
Auditing Data Provenance in Text-Generation Models Congzheng Song Vitaly Shmatikov MLAU 80 18 0 01 Nov 2018
Learning and Management for Internet-of-Things: Accounting for Adaptivity and Scalability Tianyi Chen Sergio Barbarossa Xin Wang G. Giannakis Zhi-Li Zhang 78 81 0 27 Oct 2018
Adaptive Communication Strategies to Achieve the Best Error-Runtime Trade-off in Local-Update SGD Jianyu Wang Gauri Joshi FedML 120 232 0 19 Oct 2018
Distributed Learning over Unreliable Networks Chen Yu Hanlin Tang Cédric Renggli S. Kassing Ankit Singla Dan Alistarh Ce Zhang Ji Liu OOD 105 61 0 17 Oct 2018
Collaborative Deep Learning Across Multiple Data Centers Kele Xu Haibo Mi Dawei Feng Huaimin Wang Chuan Chen Zibin Zheng Xu Lan FedML 344 18 0 16 Oct 2018
Distributed learning of deep neural network over multiple agents O. Gupta Ramesh Raskar FedML OOD 155 613 0 14 Oct 2018
Multi-Institutional Deep Learning Modeling Without Sharing Patient Data: A Feasibility Study on Brain Tumor Segmentation Micah J. Sheller G. A. Reina Brandon Edwards Jason Martin Spyridon Bakas FedML 104 474 0 10 Oct 2018
Introducing Noise in Decentralized Training of Neural Networks Linara Adilova Nathalie Paul Peter Schlicht 27 5 0 27 Sep 2018
In-Edge AI: Intelligentizing Mobile Edge Computing, Caching and Communication by Federated Learning Xiaofei Wang Yiwen Han Chenyang Wang Qiyang Zhao Xu Chen Min Chen 61 806 0 19 Sep 2018
Learning Rate Adaptation for Federated and Differentially Private Learning A. Koskela Antti Honkela FedML 81 27 0 11 Sep 2018
Deep Learning Towards Mobile Applications Ji Wang Bokai Cao Philip S. Yu Lichao Sun Weidong Bao Xiaomin Zhu HAI 92 99 0 10 Sep 2018
Universal Multi-Party Poisoning Attacks Saeed Mahloujifar Mohammad Mahmoody Ameer Mohammed AAML 66 47 0 10 Sep 2018
Towards an Intelligent Edge: Wireless Communication Meets Machine Learning Guangxu Zhu Dongzhu Liu Yuqing Du Changsheng You Jun Zhang Kaibin Huang 96 508 0 02 Sep 2018
Cooperative SGD: A unified Framework for the Design and Analysis of Communication-Efficient SGD Algorithms Jianyu Wang Gauri Joshi 198 350 0 22 Aug 2018
Don't Use Large Mini-Batches, Use Local SGD Tao R. Lin Sebastian U. Stich Kumar Kshitij Patel Martin Jaggi 133 432 0 22 Aug 2018
Privacy Amplification by Iteration Vitaly Feldman Ilya Mironov Kunal Talwar Abhradeep Thakurta FedML 108 177 0 20 Aug 2018
Mitigating Sybils in Federated Learning Poisoning Clement Fung Chris J. M. Yoon Ivan Beschastnikh AAML 75 510 0 14 Aug 2018
COLA: Decentralized Linear Learning Lie He An Bian Martin Jaggi 114 121 0 13 Aug 2018
Quantized Densely Connected U-Nets for Efficient Landmark Localization Zhiqiang Tang Xi Peng Shijie Geng Lingfei Wu Shaoting Zhang Dimitris N. Metaxas 3DV 91 142 0 07 Aug 2018
Parallel Restarted SGD with Faster Convergence and Less Communication: Demystifying Why Model Averaging Works for Deep Learning Hao Yu Sen Yang Shenghuo Zhu MoMe FedML 121 611 0 17 Jul 2018
Differentially-Private "Draw and Discard" Machine Learning Vasyl Pihur Aleksandra Korolova Frederick Liu Subhash Sankuratripati M. Yung Dachuan Huang Ruogu Zeng FedML 102 39 0 11 Jul 2018
Efficient Decentralized Deep Learning by Dynamic Model Averaging Michael Kamp Linara Adilova Joachim Sicking Fabian Hüger Peter Schlicht Tim Wirtz Stefan Wrobel 97 129 0 09 Jul 2018
Blockchain as a Service: A Decentralized and Secure Computing Paradigm G. Mendis Yifu Wu Jin Wei Moein Sabounchi Rigoberto Roche' 98 21 0 05 Jul 2018
Confidential Inference via Ternary Model Partitioning Zhongshu Gu Heqing Huang Jialong Zhang D. Su Hani Jamjoom Ankita Lamba Dimitrios E. Pendarakis Ian Molloy 103 53 0 03 Jul 2018
How To Backdoor Federated Learning Eugene Bagdasaryan Andreas Veit Yiqing Hua D. Estrin Vitaly Shmatikov SILM FedML 160 1,945 0 02 Jul 2018
ATOMO: Communication-efficient Learning via Atomic Sparsification Hongyi Wang Scott Sievert Zachary B. Charles Shengchao Liu S. Wright Dimitris Papailiopoulos 112 356 0 11 Jun 2018
Slalom: Fast, Verifiable and Private Execution of Neural Networks in Trusted Hardware Florian Tramèr Dan Boneh FedML 197 404 0 08 Jun 2018
Federated Learning with Non-IID Data Yue Zhao Meng Li Liangzhen Lai Naveen Suda Damon Civin Vikas Chandra FedML 208 2,610 0 02 Jun 2018
Robustifying Models Against Adversarial Attacks by Langevin Dynamics Vignesh Srinivasan Arturo Marbán K. Müller Wojciech Samek Shinichi Nakajima AAML 78 9 0 30 May 2018
Compact and Computationally Efficient Representation of Deep Neural Networks Simon Wiedemann K. Müller Wojciech Samek MQ 96 71 0 27 May 2018
cpSGD: Communication-efficient and differentially-private distributed SGD Naman Agarwal A. Suresh Felix X. Yu Sanjiv Kumar H. B. McMahan FedML 139 492 0 27 May 2018
Graph Oracle Models, Lower Bounds, and Gaps for Parallel Stochastic Optimization Blake E. Woodworth Jialei Wang Adam D. Smith H. B. McMahan Nathan Srebro 94 124 0 25 May 2018
LAG: Lazily Aggregated Gradient for Communication-Efficient Distributed Learning Tianyi Chen G. Giannakis Tao Sun W. Yin 64 299 0 25 May 2018
Local SGD Converges Fast and Communicates Little Sebastian U. Stich FedML 269 1,072 0 24 May 2018
Phocas: dimensional Byzantine-resilient stochastic gradient descent Cong Xie Oluwasanmi Koyejo Indranil Gupta 54 55 0 23 May 2018
Sparse Binary Compression: Towards Distributed Deep Learning with minimal Communication Felix Sattler Simon Wiedemann K. Müller Wojciech Samek MQ 68 216 0 22 May 2018
Gradient-Leaks: Understanding and Controlling Deanonymization in Federated Learning Tribhuvanesh Orekondy Seong Joon Oh Yang Zhang Bernt Schiele Mario Fritz PICV FedML 451 37 0 15 May 2018
Exploiting Unintended Feature Leakage in Collaborative Learning Luca Melis Congzheng Song Emiliano De Cristofaro Vitaly Shmatikov FedML 212 1,490 0 10 May 2018
Securing Distributed Gradient Descent in High Dimensional Statistical Learning Lili Su Jiaming Xu FedML 229 35 0 26 Apr 2018
Client Selection for Federated Learning with Heterogeneous Resources in Mobile Edge Takayuki Nishio Ryo Yonetani FedML 172 1,417 0 23 Apr 2018