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Federated Learning: Strategies for Improving Communication Efficiency

18 October 2016

Dave Bacon

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

50 / 1,868 papers shown

Title
Clustered Federated Learning: Model-Agnostic Distributed Multi-Task Optimization under Privacy Constraints Felix Sattler K. Müller Wojciech Samek FedML 212 1,019 0 04 Oct 2019
Minimax Bounds for Distributed Logistic Regression Florent Chiaroni N. Hueber FedML 32 5 0 03 Oct 2019
SAFA: a Semi-Asynchronous Protocol for Fast Federated Learning with Low Overhead A. Masullo Ligang He Toby Perrett Rui Mao Carsten Maple Majid Mirmehdi 111 319 0 03 Oct 2019
FedPAQ: A Communication-Efficient Federated Learning Method with Periodic Averaging and Quantization Amirhossein Reisizadeh Aryan Mokhtari Hamed Hassani Ali Jadbabaie Ramtin Pedarsani FedML 281 777 0 28 Sep 2019
Active Federated Learning Jack Goetz Kshitiz Malik D. Bui Seungwhan Moon Honglei Liu Anuj Kumar FedML 67 139 0 27 Sep 2019
Federated User Representation Learning D. Bui Kshitiz Malik Jack Goetz Honglei Liu Seungwhan Moon Anuj Kumar Kang G. Shin FedML 98 64 0 27 Sep 2019
Improving Federated Learning Personalization via Model Agnostic Meta Learning Yihan Jiang Jakub Konecný Keith Rush Sreeram Kannan FedML 99 606 0 27 Sep 2019
Model Pruning Enables Efficient Federated Learning on Edge Devices Yuang Jiang Shiqiang Wang Victor Valls Bongjun Ko Wei-Han Lee Kin K. Leung Leandros Tassiulas 177 471 0 26 Sep 2019
Private Aggregation from Fewer Anonymous Messages Badih Ghazi Pasin Manurangsi Rasmus Pagh A. Velingker FedML 116 57 0 24 Sep 2019
Research Directions in Democratizing Innovation through Design Automation, One-Click Manufacturing Services and Intelligent Machines B. Starly A. Angrish P. Cohen AI4CE 28 2 0 23 Sep 2019
Optimal query complexity for private sequential learning against eavesdropping Jiaming Xu Kuang Xu Dana Yang FedML 78 1 0 21 Sep 2019
Towards Federated Graph Learning for Collaborative Financial Crimes Detection Toyotaro Suzumura Yi Zhou Natahalie Barcardo Guangann Ye Keith Houck ... Yuji Watanabe Pablo S. Loyola Daniel Klyashtorny Heiko Ludwig Kumar Bhaskaran FedML 99 73 0 19 Sep 2019
Detailed comparison of communication efficiency of split learning and federated learning Abhishek Singh Praneeth Vepakomma O. Gupta Ramesh Raskar FedML 78 193 0 18 Sep 2019
From Server-Based to Client-Based Machine Learning: A Comprehensive Survey Renjie Gu Chaoyue Niu Fan Wu Guihai Chen Chun Hu Chengfei Lyu Zhihua Wu 97 26 0 18 Sep 2019
Measure Contribution of Participants in Federated Learning Guan Wang Charlie Xiaoqian Dang Ziye Zhou FedML 111 200 0 17 Sep 2019
Communication-Efficient Distributed Learning via Lazily Aggregated Quantized Gradients Jun Sun Tianyi Chen G. Giannakis Zaiyue Yang 88 95 0 17 Sep 2019
A Joint Learning and Communications Framework for Federated Learning over Wireless Networks Mingzhe Chen Zhaohui Yang Walid Saad Changchuan Yin H. Vincent Poor Shuguang Cui FedML 115 1,199 0 17 Sep 2019
BAFFLE : Blockchain Based Aggregator Free Federated Learning P. Ramanan K. Nakayama FedML 61 173 0 16 Sep 2019
Communication-Efficient Distributed Optimization in Networks with Gradient Tracking and Variance Reduction Boyue Li Shicong Cen Yuxin Chen Yuejie Chi 64 12 0 12 Sep 2019
Byzantine-Robust Federated Machine Learning through Adaptive Model Averaging Luis Muñoz-González Kenneth T. Co Emil C. Lupu FedML 85 186 0 11 Sep 2019
Tighter Theory for Local SGD on Identical and Heterogeneous Data Ahmed Khaled Konstantin Mishchenko Peter Richtárik 102 435 0 10 Sep 2019
Gradient Descent with Compressed Iterates Ahmed Khaled Peter Richtárik 43 22 0 10 Sep 2019
First Analysis of Local GD on Heterogeneous Data Ahmed Khaled Konstantin Mishchenko Peter Richtárik FedML 111 172 0 10 Sep 2019
Privacy-Preserving Bandits Mohammad Malekzadeh D. Athanasakis Hamed Haddadi B. Livshits 142 18 0 10 Sep 2019
Communication-Censored Distributed Stochastic Gradient Descent Weiyu Li Tianyi Chen Liping Li Zhaoxian Wu Qing Ling 55 17 0 09 Sep 2019
Convex Set Disjointness, Distributed Learning of Halfspaces, and LP Feasibility M. Braverman Gillat Kol Shay Moran Raghuvansh R. Saxena 35 6 0 08 Sep 2019
Distributed Deep Learning with Event-Triggered Communication Jemin George Prudhvi K. Gurram 56 16 0 08 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 115 621 0 02 Sep 2019
Rewarding High-Quality Data via Influence Functions A. Richardson Aris Filos-Ratsikas Boi Faltings FedML TDI 82 40 0 30 Aug 2019
An End-to-End Encrypted Neural Network for Gradient Updates Transmission in Federated Learning Hongyu Li Tianqi Han FedML 71 32 0 22 Aug 2019
RATQ: A Universal Fixed-Length Quantizer for Stochastic Optimization Prathamesh Mayekar Himanshu Tyagi MQ 79 49 0 22 Aug 2019
BRIDGE: Byzantine-resilient Decentralized Gradient Descent Cheng Fang Zhixiong Yang W. Bajwa 98 102 0 21 Aug 2019
Federated Learning: Challenges, Methods, and Future Directions Tian Li Anit Kumar Sahu Ameet Talwalkar Virginia Smith FedML 199 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
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
Adaptive Kernel Learning in Heterogeneous Networks Hrusikesha Pradhan Amrit Singh Bedi Alec Koppel K. Rajawat 56 7 0 01 Aug 2019
A Federated Learning Approach for Mobile Packet Classification Evita Bakopoulou Bálint Tillman A. Markopoulou 62 30 0 30 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
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
ShrinkML: End-to-End ASR Model Compression Using Reinforcement Learning Łukasz Dudziak Mohamed S. Abdelfattah Ravichander Vipperla Stefanos Laskaridis Nicholas D. Lane OffRL 106 18 0 08 Jul 2019
On the Convergence of FedAvg on Non-IID Data Xiang Li Kaixuan Huang Wenhao Yang Shusen Wang Zhihua Zhang FedML 258 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 66 198 0 02 Jul 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
Active Learning Solution on Distributed Edge Computing Jia Qian Sayantani Sengupta Lars Kai Hansen 56 20 0 25 Jun 2019
Deep Leakage from Gradients Ligeng Zhu Zhijian Liu Song Han FedML 114 2,249 0 21 Jun 2019