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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
Distributed Deep Learning with Event-Triggered Communication Jemin George Prudhvi K. Gurram 58 16 0 08 Sep 2019
The Disruptions of 5G on Data-driven Technologies and Applications Dumitrel Loghin Shaofeng Cai Gang Chen Tien Tuan Anh Dinh Feiyi Fan ... Wei Wang Xiaokui Xiao Yang Yang Meihui Zhang Zhonghua Zhang 66 66 0 06 Sep 2019
Hierarchical Federated Learning Across Heterogeneous Cellular Networks Mehdi Salehi Heydar Abad Emre Ozfatura Deniz Gunduz Ozgur Ercetin FedML 143 314 0 05 Sep 2019
Edge Intelligence: The Confluence of Edge Computing and Artificial Intelligence Shuiguang Deng Hailiang Zhao Weijia Fang Yuxiang Cai Schahram Dustdar Albert Y. Zomaya 120 621 0 02 Sep 2019
GADMM: Fast and Communication Efficient Framework for Distributed Machine Learning Anis Elgabli Jihong Park Amrit Singh Bedi M. Bennis Vaneet Aggarwal FedML 89 83 0 30 Aug 2019
Key Protected Classification for Collaborative Learning Mert Bulent Sariyildiz R. G. Cinbis Erman Ayday 51 10 0 27 Aug 2019
Federated Learning: Challenges, Methods, and Future Directions Tian Li Anit Kumar Sahu Ameet Talwalkar Virginia Smith FedML 217 4,584 0 21 Aug 2019
Decentralized Federated Learning: A Segmented Gossip Approach Chenghao Hu Jingyan Jiang Zhi Wang FedML 73 188 0 21 Aug 2019
Towards Effective Device-Aware Federated Learning Vito Walter Anelli Yashar Deldjoo Tommaso Di Noia Antonio Ferrara FedML 57 31 0 20 Aug 2019
Distilling On-Device Intelligence at the Network Edge Jihong Park Shiqiang Wang Anis Elgabli Seungeun Oh Eunjeong Jeong Han Cha Hyesung Kim Seong-Lyun Kim M. Bennis 73 32 0 16 Aug 2019
Federated Learning with Additional Mechanisms on Clients to Reduce Communication Costs Xin Yao Tianchi Huang Chenglei Wu Ruixiao Zhang Lifeng Sun FedML 73 38 0 16 Aug 2019
Two-stage Federated Phenotyping and Patient Representation Learning Dianbo Liu Dmitriy Dligach Timothy A. Miller 71 82 0 14 Aug 2019
On Convergence of Distributed Approximate Newton Methods: Globalization, Sharper Bounds and Beyond Xiao-Tong Yuan Ping Li 144 32 0 06 Aug 2019
Motivating Workers in Federated Learning: A Stackelberg Game Perspective Y. Sarikaya Ozgur Ercetin FedML 77 187 0 06 Aug 2019
Machine Learning at the Network Edge: A Survey M. G. Sarwar Murshed Chris Murphy Daqing Hou Nazar Khan Ganesh Ananthanarayanan Faraz Hussain 98 393 0 31 Jul 2019
Federated Learning for Wireless Communications: Motivation, Opportunities and Challenges Solmaz Niknam Harpreet S. Dhillon J. H. Reed 104 613 0 30 Jul 2019
A Federated Learning Approach for Mobile Packet Classification Evita Bakopoulou Bálint Tillman A. Markopoulou 62 30 0 30 Jul 2019
DeepCABAC: A Universal Compression Algorithm for Deep Neural Networks Simon Wiedemann H. Kirchhoffer Stefan Matlage Paul Haase Arturo Marbán ... Ahmed Osman D. Marpe H. Schwarz Thomas Wiegand Wojciech Samek 111 98 0 27 Jul 2019
Boosting Privately: Privacy-Preserving Federated Extreme Boosting for Mobile Crowdsensing Yang Liu Zhuo Ma Ximeng Liu Siqi Ma Surya Nepal R. Deng FedML 64 64 0 24 Jul 2019
Federated Learning over Wireless Fading Channels M. Amiri Deniz Gunduz 132 516 0 23 Jul 2019
A Survey on Federated Learning Systems: Vision, Hype and Reality for Data Privacy and Protection Yue Liu Zeyi Wen Zhaomin Wu Sixu Hu Naibo Wang Yuan N. Li Xu Liu Bingsheng He FedML 130 1,016 0 23 Jul 2019
Decentralized Deep Learning with Arbitrary Communication Compression Anastasia Koloskova Tao R. Lin Sebastian U. Stich Martin Jaggi FedML 119 236 0 22 Jul 2019
FedHealth: A Federated Transfer Learning Framework for Wearable Healthcare Yiqiang Chen Jindong Wang Chaohui Yu Wen Gao Xin Qin FedML 117 725 0 22 Jul 2019
Convergence of Edge Computing and Deep Learning: A Comprehensive Survey Xiaofei Wang Yiwen Han Victor C. M. Leung Dusit Niyato Xueqiang Yan Xu Chen 113 1,006 0 19 Jul 2019
Federated Principal Component Analysis Andreas Grammenos R. Mendoza-Smith Jon Crowcroft Cecilia Mascolo FedML 138 11 0 18 Jul 2019
The Tradeoff Between Privacy and Accuracy in Anomaly Detection Using Federated XGBoost Mengwei Yang Linqi Song Jie Xu Congduan Li Guozhen Tan FedML 126 31 0 16 Jul 2019
Federated Reinforcement Distillation with Proxy Experience Memory Han Cha Jihong Park Hyesung Kim Seong-Lyun Kim M. Bennis 99 16 0 15 Jul 2019
Multi-hop Federated Private Data Augmentation with Sample Compression Eunjeong Jeong Seungeun Oh Jihong Park Hyesung Kim M. Bennis Seong-Lyun Kim 82 17 0 15 Jul 2019
Energy-Efficient Radio Resource Allocation for Federated Edge Learning Qunsong Zeng Yuqing Du K. Leung Kaibin Huang 83 230 0 13 Jul 2019
Privacy-Preserving Classification with Secret Vector Machines Valentin Hartmann Konark Modi J. M. Pujol Robert West 85 14 0 08 Jul 2019
Wireless Federated Distillation for Distributed Edge Learning with Heterogeneous Data Jinhyun Ahn Osvaldo Simeone Joonhyuk Kang FedML 67 109 0 05 Jul 2019
On the Convergence of FedAvg on Non-IID Data Xiang Li Kaixuan Huang Wenhao Yang Shusen Wang Zhihua Zhang FedML 302 2,368 0 04 Jul 2019
Astraea: Self-balancing Federated Learning for Improving Classification Accuracy of Mobile Deep Learning Applications Moming Duan Duo Liu Xianzhang Chen Yujuan Tan Jinting Ren Lei Qiao Liang Liang FedML 74 198 0 02 Jul 2019
Proof of Witness Presence: Blockchain Consensus for Augmented Democracy in Smart Cities Evangelos Pournaras 169 65 0 30 Jun 2019
Privacy-Preserving Blockchain-Based Federated Learning for IoT Devices Yang Zhao Jun Zhao Linshan Jiang Rui Tan Dusit Niyato Zengxiang Li Lingjuan Lyu Yingbo Liu 88 105 0 26 Jun 2019
Privacy Preserving QoE Modeling using Collaborative Learning Selim Ickin K. Vandikas M. Fiedler 28 22 0 21 Jun 2019
Deep Leakage from Gradients Ligeng Zhu Zhijian Liu Song Han FedML 114 2,249 0 21 Jun 2019
Scalable and Differentially Private Distributed Aggregation in the Shuffled Model Badih Ghazi Rasmus Pagh A. Velingker FedML 105 98 0 19 Jun 2019
Robust Federated Learning in a Heterogeneous Environment Avishek Ghosh Justin Hong Dong Yin Kannan Ramchandran OOD FedML 79 221 0 16 Jun 2019
Variational Federated Multi-Task Learning Luca Corinzia Ami Beuret J. M. Buhmann FedML 115 161 0 14 Jun 2019
Federated Learning for Emoji Prediction in a Mobile Keyboard Swaroop Indra Ramaswamy Rajiv Mathews Kanishka Rao Franccoise Beaufays FedML 73 313 0 11 Jun 2019
Performance Analysis and Characterization of Training Deep Learning Models on Mobile Devices Jie Liu Jiawen Liu Wan Du Dong Li HAI 52 5 0 10 Jun 2019
Towards Sharp Analysis for Distributed Learning with Random Features Jian Li Yong Liu Weiping Wang 74 3 0 07 Jun 2019
Adaptive Gradient-Based Meta-Learning Methods M. Khodak Maria-Florina Balcan Ameet Talwalkar FedML 141 356 0 06 Jun 2019
Qsparse-local-SGD: Distributed SGD with Quantization, Sparsification, and Local Computations Debraj Basu Deepesh Data C. Karakuş Suhas Diggavi MQ 76 408 0 06 Jun 2019
Distributed Training with Heterogeneous Data: Bridging Median- and Mean-Based Algorithms Xiangyi Chen Tiancong Chen Haoran Sun Zhiwei Steven Wu Mingyi Hong FedML 64 74 0 04 Jun 2019
Towards Fair and Privacy-Preserving Federated Deep Models Lingjuan Lyu Jiangshan Yu Karthik Nandakumar Yitong Li Xingjun Ma Jiong Jin Han Yu Kee Siong Ng FedML 52 20 0 04 Jun 2019
P3SGD: Patient Privacy Preserving SGD for Regularizing Deep CNNs in Pathological Image Classification Bingzhe Wu Shiwan Zhao Guangyu Sun Xiaolu Zhang Zhong Su C. Zeng Zhihong Liu 80 41 0 30 May 2019
Differential Privacy Has Disparate Impact on Model Accuracy Eugene Bagdasaryan Vitaly Shmatikov 171 485 0 28 May 2019
Bayesian Nonparametric Federated Learning of Neural Networks Mikhail Yurochkin Mayank Agarwal S. Ghosh Kristjan Greenewald T. Hoang Y. Khazaeni FedML 159 732 0 28 May 2019