Communication-Efficient Device Scheduling for Federated Learning Using Lyapunov Optimization

1 March 2025

Papers citing "Communication-Efficient Device Scheduling for Federated Learning Using Lyapunov Optimization"

33 / 33 papers shown

Title
A Unified Analysis of Federated Learning with Arbitrary Client Participation Shiqiang Wang Mingyue Ji FedML 109 58 0 31 Dec 2024
Federated Learning with Flexible Control Shiqiang Wang Jake B. Perazzone Mingyue Ji Kevin S. Chan FedML 71 18 0 16 Dec 2022
Communication-Efficient Device Scheduling for Federated Learning Using Stochastic Optimization Jake B. Perazzone Shiqiang Wang Mingyue Ji Kevin S. Chan FedML 59 76 0 19 Jan 2022
Optimal Rate Adaption in Federated Learning with Compressed Communications Laizhong Cui Xiaoxin Su Yipeng Zhou Jiangchuan Liu FedML 85 41 0 13 Dec 2021
Fast Federated Learning in the Presence of Arbitrary Device Unavailability Xinran Gu Kaixuan Huang Jingzhao Zhang Longbo Huang FedML 59 101 0 08 Jun 2021
Clustered Sampling: Low-Variance and Improved Representativity for Clients Selection in Federated Learning Yann Fraboni Richard Vidal Laetitia Kameni Marco Lorenzi FedML 60 193 0 12 May 2021
Linear Convergence in Federated Learning: Tackling Client Heterogeneity and Sparse Gradients A. Mitra Rayana H. Jaafar George J. Pappas Hamed Hassani FedML 101 159 0 14 Feb 2021
Achieving Linear Speedup with Partial Worker Participation in Non-IID Federated Learning Haibo Yang Minghong Fang Jia Liu FedML 66 258 0 27 Jan 2021
An Efficiency-boosting Client Selection Scheme for Federated Learning with Fairness Guarantee Tiansheng Huang Weiwei Lin Wentai Wu Ligang He Keqin Li Albert Y. Zomaya FedML 126 228 0 03 Nov 2020
Optimal Gradient Compression for Distributed and Federated Learning Alyazeed Albasyoni M. Safaryan Laurent Condat Peter Richtárik FedML 51 64 0 07 Oct 2020
Communication-Efficient Federated Learning via Optimal Client Sampling Mónica Ribero H. Vikalo FedML 57 95 0 30 Jul 2020
Joint Device Scheduling and Resource Allocation for Latency Constrained Wireless Federated Learning Wenqi Shi Sheng Zhou Z. Niu Miao Jiang Lu Geng 57 297 0 14 Jul 2020
Scheduling for Cellular Federated Edge Learning with Importance and Channel Awareness Jinke Ren Yinghui He Dingzhu Wen Guanding Yu Kaibin Huang Dongning Guo 88 196 0 01 Apr 2020
Adaptive Federated Optimization Sashank J. Reddi Zachary B. Charles Manzil Zaheer Zachary Garrett Keith Rush Jakub Konecný Sanjiv Kumar H. B. McMahan FedML 179 1,448 0 29 Feb 2020
Adaptive Gradient Sparsification for Efficient Federated Learning: An Online Learning Approach Pengchao Han Shiqiang Wang K. Leung FedML 74 179 0 14 Jan 2020
Energy Efficient Federated Learning Over Wireless Communication Networks Zhaohui Yang Mingzhe Chen Walid Saad Choong Seon Hong M. Shikh-Bahaei 79 693 0 06 Nov 2019
FedPAQ: A Communication-Efficient Federated Learning Method with Periodic Averaging and Quantization Amirhossein Reisizadeh Aryan Mokhtari Hamed Hassani Ali Jadbabaie Ramtin Pedarsani FedML 254 774 0 28 Sep 2019
Active Federated Learning Jack Goetz Kshitiz Malik D. Bui Seungwhan Moon Honglei Liu Anuj Kumar FedML 52 137 0 27 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 76 1,189 0 17 Sep 2019
Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification T. Hsu Qi Matthew Brown FedML 143 1,157 0 13 Sep 2019
On the Convergence of FedAvg on Non-IID Data Xiang Li Kaixuan Huang Wenhao Yang Shusen Wang Zhihua Zhang FedML 147 2,343 0 04 Jul 2019
Robust and Communication-Efficient Federated Learning from Non-IID Data Felix Sattler Simon Wiedemann K. Müller Wojciech Samek FedML 74 1,361 0 07 Mar 2019
Federated Optimization in Heterogeneous Networks Tian Li Anit Kumar Sahu Manzil Zaheer Maziar Sanjabi Ameet Talwalkar Virginia Smith FedML 180 5,208 0 14 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 59 899 0 07 Dec 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 79 608 0 17 Jul 2018
Client Selection for Federated Learning with Heterogeneous Resources in Mobile Edge Takayuki Nishio Ryo Yonetani FedML 120 1,404 0 23 Apr 2018
Adaptive Federated Learning in Resource Constrained Edge Computing Systems Shiqiang Wang Tiffany Tuor Theodoros Salonidis K. Leung C. Makaya T. He Kevin S. Chan 254 1,709 0 14 Apr 2018
Differentially Private Federated Learning: A Client Level Perspective Robin C. Geyer T. Klein Moin Nabi FedML 133 1,297 0 20 Dec 2017
Can Decentralized Algorithms Outperform Centralized Algorithms? A Case Study for Decentralized Parallel Stochastic Gradient Descent Xiangru Lian Ce Zhang Huan Zhang Cho-Jui Hsieh Wei Zhang Ji Liu 50 1,233 0 25 May 2017
Federated Learning: Strategies for Improving Communication Efficiency Jakub Konecný H. B. McMahan Felix X. Yu Peter Richtárik A. Suresh Dave Bacon FedML 306 4,649 0 18 Oct 2016
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima N. Keskar Dheevatsa Mudigere J. Nocedal M. Smelyanskiy P. T. P. Tang ODL 427 2,945 0 15 Sep 2016
Communication-Efficient Learning of Deep Networks from Decentralized Data H. B. McMahan Eider Moore Daniel Ramage S. Hampson Blaise Agüera y Arcas FedML 406 17,559 0 17 Feb 2016
Manopt, a Matlab toolbox for optimization on manifolds Nicolas Boumal Bamdev Mishra P.-A. Absil R. Sepulchre 102 1,031 0 23 Aug 2013