Federated learning compression designed for lightweight communications

Federated learning compression designed for lightweight communications

23 October 2023

Lucas Grativol Ribeiro

Mathieu Léonardon

Guillaume Muller

Virginie Fresse

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Papers citing "Federated learning compression designed for lightweight communications"

14 / 14 papers shown

Title
AnycostFL: Efficient On-Demand Federated Learning over Heterogeneous Edge Devices Peichun Li Guoliang Cheng Xumin Huang Jiawen Kang Rong Yu Yuan Wu Miao Pan FedML 99 22 0 08 Jan 2023
ZeroFL: Efficient On-Device Training for Federated Learning with Local Sparsity Xinchi Qiu Javier Fernandez-Marques Pedro Gusmão Yan Gao Titouan Parcollet Nicholas D. Lane FedML 69 71 0 04 Aug 2022
On-Device Training Under 256KB Memory Ji Lin Ligeng Zhu Wei-Ming Chen Wei-Chen Wang Chuang Gan Song Han MQ 88 207 0 30 Jun 2022
Sparsity in Deep Learning: Pruning and growth for efficient inference and training in neural networks Torsten Hoefler Dan Alistarh Tal Ben-Nun Nikoli Dryden Alexandra Peste MQ 314 720 0 31 Jan 2021
Rethinking Weight Decay For Efficient Neural Network Pruning Hugo Tessier Vincent Gripon Mathieu Léonardon M. Arzel T. Hannagan David Bertrand 81 26 0 20 Nov 2020
Flower: A Friendly Federated Learning Research Framework Daniel J. Beutel Taner Topal Akhil Mathur Xinchi Qiu Javier Fernandez-Marques ... Lorenzo Sani Kwing Hei Li Titouan Parcollet Pedro Porto Buarque de Gusmão Nicholas D. Lane FedML 136 809 0 28 Jul 2020
Adaptive Federated Optimization Sashank J. Reddi Zachary B. Charles Manzil Zaheer Zachary Garrett Keith Rush Jakub Konecný Sanjiv Kumar H. B. McMahan FedML 177 1,437 0 29 Feb 2020
Sparse Weight Activation Training Md Aamir Raihan Tor M. Aamodt 91 73 0 07 Jan 2020
Advances and Open Problems in Federated Learning Peter Kairouz H. B. McMahan Brendan Avent A. Bellet M. Bennis ... Zheng Xu Qiang Yang Felix X. Yu Han Yu Sen Zhao FedML AI4CE 256 6,261 0 10 Dec 2019
Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification T. Hsu Qi Matthew Brown FedML 143 1,150 0 13 Sep 2019
A Survey of Model Compression and Acceleration for Deep Neural Networks Yu Cheng Duo Wang Pan Zhou Zhang Tao 74 1,095 0 23 Oct 2017
Communication-Efficient Learning of Deep Networks from Decentralized Data H. B. McMahan Eider Moore Daniel Ramage S. Hampson Blaise Agüera y Arcas FedML 406 17,486 0 17 Feb 2016
BinaryConnect: Training Deep Neural Networks with binary weights during propagations Matthieu Courbariaux Yoshua Bengio J. David MQ 209 2,985 0 02 Nov 2015
Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding Song Han Huizi Mao W. Dally 3DGS 259 8,842 0 01 Oct 2015