Expanding the Reach of Federated Learning by Reducing Client Resource Requirements

18 December 2018

Papers citing "Expanding the Reach of Federated Learning by Reducing Client Resource Requirements"

32 / 82 papers shown

Title
A Payload Optimization Method for Federated Recommender Systems Farwa K. Khan Adrian Flanagan K. E. Tan Z. Alamgir Muhammad Ammad-ud-din 82 29 0 27 Jul 2021
Federated Learning with Downlink Device Selection M. Amiri Sanjeev R. Kulkarni H. Vincent Poor FedML 18 9 0 07 Jul 2021
Loss Tolerant Federated Learning Pengyuan Zhou Pei Fang Pan Hui 13 16 0 08 May 2021
From Distributed Machine Learning to Federated Learning: A Survey Ji Liu Jizhou Huang Yang Zhou Xuhong Li Shilei Ji Haoyi Xiong Dejing Dou FedML OOD 56 244 0 29 Apr 2021
Distributed Learning in Wireless Networks: Recent Progress and Future Challenges Mingzhe Chen Deniz Gündüz Kaibin Huang Walid Saad M. Bennis Aneta Vulgarakis Feljan H. Vincent Poor 45 402 0 05 Apr 2021
Efficient Randomized Subspace Embeddings for Distributed Optimization under a Communication Budget R. Saha Mert Pilanci Andrea J. Goldsmith 34 5 0 13 Mar 2021
FjORD: Fair and Accurate Federated Learning under heterogeneous targets with Ordered Dropout Samuel Horváth Stefanos Laskaridis Mario Almeida Ilias Leondiadis Stylianos I. Venieris Nicholas D. Lane 189 268 0 26 Feb 2021
Fairness and Accuracy in Federated Learning Wei Huang Tianrui Li Dexian Wang Shengdong Du Junbo Zhang FedML 39 52 0 18 Dec 2020
Federated Learning under Importance Sampling Elsa Rizk Stefan Vlaski Ali H. Sayed FedML 18 52 0 14 Dec 2020
Design and Analysis of Uplink and Downlink Communications for Federated Learning Sihui Zheng Cong Shen Xiang Chen 39 140 0 07 Dec 2020
CatFedAvg: Optimising Communication-efficiency and Classification Accuracy in Federated Learning D. Sarkar Sumit Rai Ankur Narang FedML 26 2 0 14 Nov 2020
Throughput-Optimal Topology Design for Cross-Silo Federated Learning Othmane Marfoq Chuan Xu Giovanni Neglia Richard Vidal FedML 67 85 0 23 Oct 2020
Breaking the Communication-Privacy-Accuracy Trilemma Wei-Ning Chen Peter Kairouz Ayfer Özgür 14 116 0 22 Jul 2020
A Systematic Literature Review on Federated Machine Learning: From A Software Engineering Perspective Sin Kit Lo Qinghua Lu Chen Wang Hye-Young Paik Liming Zhu FedML 48 83 0 22 Jul 2020
Robust Federated Learning: The Case of Affine Distribution Shifts Amirhossein Reisizadeh Farzan Farnia Ramtin Pedarsani Ali Jadbabaie FedML OOD 32 162 0 16 Jun 2020
Communication Efficient Federated Learning with Energy Awareness over Wireless Networks Richeng Jin Xiaofan He H. Dai 36 25 0 15 Apr 2020
HFEL: Joint Edge Association and Resource Allocation for Cost-Efficient Hierarchical Federated Edge Learning Siqi Luo Xu Chen Qiong Wu Zhi Zhou Shuai Yu FedML 33 339 0 26 Feb 2020
Uncertainty Principle for Communication Compression in Distributed and Federated Learning and the Search for an Optimal Compressor M. Safaryan Egor Shulgin Peter Richtárik 32 61 0 20 Feb 2020
Dynamic Federated Learning Elsa Rizk Stefan Vlaski Ali H. Sayed FedML 22 25 0 20 Feb 2020
Faster On-Device Training Using New Federated Momentum Algorithm Zhouyuan Huo Qian Yang Bin Gu Heng-Chiao Huang FedML 22 47 0 06 Feb 2020
Adaptive Gradient Sparsification for Efficient Federated Learning: An Online Learning Approach Pengchao Han Shiqiang Wang K. Leung FedML 35 175 0 14 Jan 2020
Helios: Heterogeneity-Aware Federated Learning with Dynamically Balanced Collaboration Zirui Xu Zhao Yang Jinjun Xiong Xiang Chen FedML 24 58 0 03 Dec 2019
Secure Federated Submodel Learning Chaoyue Niu Fan Wu Shaojie Tang Lifeng Hua Rongfei Jia Chengfei Lv Zhihua Wu Guihai Chen FedML 14 30 0 06 Nov 2019
Clustered Federated Learning: Model-Agnostic Distributed Multi-Task Optimization under Privacy Constraints Felix Sattler K. Müller Wojciech Samek FedML 71 969 0 04 Oct 2019
Federated User Representation Learning D. Bui Kshitiz Malik Jack Goetz Honglei Liu Seungwhan Moon Anuj Kumar Kang G. Shin FedML 30 63 0 27 Sep 2019
Improving Federated Learning Personalization via Model Agnostic Meta Learning Yihan Jiang Jakub Konecný Keith Rush Sreeram Kannan FedML 21 589 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 38 447 0 26 Sep 2019
Gradient Descent with Compressed Iterates Ahmed Khaled Peter Richtárik 21 22 0 10 Sep 2019
Federated Learning with Additional Mechanisms on Clients to Reduce Communication Costs Xin Yao Tianchi Huang Chenglei Wu Ruixiao Zhang Lifeng Sun FedML 18 38 0 16 Aug 2019
A Federated Learning Approach for Mobile Packet Classification Evita Bakopoulou Bálint Tillman A. Markopoulou 21 30 0 30 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 17 977 0 19 Jul 2019
PowerSGD: Practical Low-Rank Gradient Compression for Distributed Optimization Thijs Vogels Sai Praneeth Karimireddy Martin Jaggi 19 317 0 31 May 2019