Communication-Efficient Learning of Deep Networks from Decentralized Data

17 February 2016

Blaise Agüera y Arcas

FedML

ArXiv PDF HTML

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

50 / 2,727 papers shown

Title
Broadband Analog Aggregation for Low-Latency Federated Edge Learning (Extended Version) Guangxu Zhu Yong Wang Kaibin Huang FedML 43 638 0 30 Dec 2018
Entropy-Constrained Training of Deep Neural Networks Simon Wiedemann Arturo Marbán K. Müller Wojciech Samek 27 27 0 18 Dec 2018
Learning Private Neural Language Modeling with Attentive Aggregation Shaoxiong Ji Shirui Pan Guodong Long Xue Li Jing Jiang Zi Huang FedML MoMe 24 139 0 17 Dec 2018
Stochastic Distributed Optimization for Machine Learning from Decentralized Features Yaochen Hu Di Niu Jianming Yang Shengping Zhou 24 5 0 16 Dec 2018
No Peek: A Survey of private distributed deep learning Praneeth Vepakomma Tristan Swedish Ramesh Raskar O. Gupta Abhimanyu Dubey SyDa FedML 35 100 0 08 Dec 2018
Communication-Efficient Policy Gradient Methods for Distributed Reinforcement Learning Tianyi Chen Kai Zhang G. Giannakis Tamer Basar OffRL 34 41 0 07 Dec 2018
A Hybrid Approach to Privacy-Preserving Federated Learning Stacey Truex Nathalie Baracaldo Ali Anwar Thomas Steinke Heiko Ludwig Rui Zhang Yi Zhou FedML 31 884 0 07 Dec 2018
Wireless Network Intelligence at the Edge Jihong Park S. Samarakoon M. Bennis Mérouane Debbah 33 518 0 07 Dec 2018
Wireless Data Acquisition for Edge Learning: Data-Importance Aware Retransmission Dongzhu Liu Guangxu Zhu Jun Zhang Kaibin Huang 21 41 0 05 Dec 2018
LEAF: A Benchmark for Federated Settings S. Caldas Sai Meher Karthik Duddu Peter Wu Tian Li Jakub Konecný H. B. McMahan Virginia Smith Ameet Talwalkar FedML 64 1,398 0 03 Dec 2018
Protection Against Reconstruction and Its Applications in Private Federated Learning Abhishek Bhowmick John C. Duchi Julien Freudiger Gaurav Kapoor Ryan M. Rogers FedML 32 358 0 03 Dec 2018
Comprehensive Privacy Analysis of Deep Learning: Passive and Active White-box Inference Attacks against Centralized and Federated Learning Milad Nasr Reza Shokri Amir Houmansadr FedML MIACV AAML 13 244 0 03 Dec 2018
Split learning for health: Distributed deep learning without sharing raw patient data Praneeth Vepakomma O. Gupta Tristan Swedish Ramesh Raskar FedML 63 693 0 03 Dec 2018
Beyond Inferring Class Representatives: User-Level Privacy Leakage From Federated Learning Peng Kuang Mengkai Song Zhifei Zhang Yang Song Qian Wang Hairong Qi FedML 31 779 0 03 Dec 2018
Analyzing Federated Learning through an Adversarial Lens A. Bhagoji Supriyo Chakraborty Prateek Mittal S. Calo FedML 193 1,037 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 28 596 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 32 55 0 27 Nov 2018
An overview of deep learning in medical imaging focusing on MRI A. Lundervold A. Lundervold OOD 27 1,619 0 25 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 82 1,518 0 08 Nov 2018
Adaptive Communication Strategies to Achieve the Best Error-Runtime Trade-off in Local-Update SGD Jianyu Wang Gauri Joshi FedML 38 232 0 19 Oct 2018
Collaborative Deep Learning Across Multiple Data Centers Kele Xu Haibo Mi Dawei Feng Huaimin Wang Chuan Chen Zibin Zheng Xu Lan FedML 215 18 0 16 Oct 2018
Distributed learning of deep neural network over multiple agents O. Gupta Ramesh Raskar FedML OOD 28 599 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 29 457 0 10 Oct 2018
Effective Parallelisation for Machine Learning Michael Kamp Mario Boley Olana Missura Thomas Gärtner 14 12 0 08 Oct 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 19 798 0 19 Sep 2018
Learning Rate Adaptation for Federated and Differentially Private Learning A. Koskela Antti Honkela FedML 27 27 0 11 Sep 2018
Deep Learning Towards Mobile Applications Ji Wang Bokai Cao Philip S. Yu Lichao Sun Weidong Bao Xiaomin Zhu HAI 32 98 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 20 505 0 02 Sep 2018
Cooperative SGD: A unified Framework for the Design and Analysis of Communication-Efficient SGD Algorithms Jianyu Wang Gauri Joshi 38 348 0 22 Aug 2018
Don't Use Large Mini-Batches, Use Local SGD Tao R. Lin Sebastian U. Stich Kumar Kshitij Patel Martin Jaggi 80 431 0 22 Aug 2018
Privacy Amplification by Iteration Vitaly Feldman Ilya Mironov Kunal Talwar Abhradeep Thakurta FedML 31 171 0 20 Aug 2018
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 Lie He An Bian Martin Jaggi 53 118 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 19 143 0 07 Aug 2018
Differentially-Private "Draw and Discard" Machine Learning Vasyl Pihur Aleksandra Korolova Frederick Liu Subhash Sankuratripati M. Yung Dachuan Huang Ruogu Zeng FedML 38 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 37 129 0 09 Jul 2018
Blockchain as a Service: A Decentralized and Secure Computing Paradigm G. Mendis Yifu Wu Jin Wei Moein Sabounchi Rigoberto Roche' 32 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 24 53 0 03 Jul 2018
Federated Learning with Non-IID Data Yue Zhao Meng Li Liangzhen Lai Naveen Suda Damon Civin Vikas Chandra FedML 82 2,534 0 02 Jun 2018
Robustifying Models Against Adversarial Attacks by Langevin Dynamics Vignesh Srinivasan Arturo Marbán K. Müller Wojciech Samek Shinichi Nakajima AAML 38 9 0 30 May 2018
Compact and Computationally Efficient Representation of Deep Neural Networks Simon Wiedemann K. Müller Wojciech Samek MQ 42 68 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 30 488 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 35 123 0 25 May 2018
LAG: Lazily Aggregated Gradient for Communication-Efficient Distributed Learning Tianyi Chen G. Giannakis Tao Sun W. Yin 36 297 0 25 May 2018
Local SGD Converges Fast and Communicates Little Sebastian U. Stich FedML 93 1,050 0 24 May 2018
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 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 Luca Melis Congzheng Song Emiliano De Cristofaro Vitaly Shmatikov FedML 98 1,457 0 10 May 2018
Securing Distributed Gradient Descent in High Dimensional Statistical Learning Lili Su Jiaming Xu FedML 143 35 0 26 Apr 2018
Client Selection for Federated Learning with Heterogeneous Resources in Mobile Edge Takayuki Nishio Ryo Yonetani FedML 78 5 0 23 Apr 2018