Communication Optimization in Large Scale Federated Learning using
Autoencoder Compressed Weight Updates

Communication Optimization in Large Scale Federated Learning using Autoencoder Compressed Weight Updates

12 August 2021

Srikanth Chandar

Pravin Chandran

Raghavendra Bhat

Avinash Chakravarthi

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Papers citing "Communication Optimization in Large Scale Federated Learning using Autoencoder Compressed Weight Updates"

15 / 15 papers shown

Title
FEDZIP: A Compression Framework for Communication-Efficient Federated Learning Amirhossein Malekijoo Mohammad Javad Fadaeieslam Hanieh Malekijou Morteza Homayounfar F. Alizadeh-Shabdiz Reza Rawassizadeh FedML 84 55 0 02 Feb 2021
Federated Knowledge Distillation Hyowoon Seo Jihong Park Seungeun Oh M. Bennis Seong-Lyun Kim FedML 96 92 0 04 Nov 2020
ALF: Autoencoder-based Low-rank Filter-sharing for Efficient Convolutional Neural Networks Alexander Frickenstein M. Vemparala Nael Fasfous Laura Hauenschild N. S. Nagaraja C. Unger W. Stechele 45 5 0 27 Jul 2020
FetchSGD: Communication-Efficient Federated Learning with Sketching D. Rothchild Ashwinee Panda Enayat Ullah Nikita Ivkin Ion Stoica Vladimir Braverman Joseph E. Gonzalez Raman Arora FedML 97 370 0 15 Jul 2020
FedMAX: Mitigating Activation Divergence for Accurate and Communication-Efficient Federated Learning Wei Chen Kartikeya Bhardwaj R. Marculescu FedML 53 38 0 07 Apr 2020
Federated Learning with Matched Averaging Hongyi Wang Mikhail Yurochkin Yuekai Sun Dimitris Papailiopoulos Y. Khazaeni FedML 124 1,129 0 15 Feb 2020
FedPAQ: A Communication-Efficient Federated Learning Method with Periodic Averaging and Quantization Amirhossein Reisizadeh Aryan Mokhtari Hamed Hassani Ali Jadbabaie Ramtin Pedarsani FedML 260 774 0 28 Sep 2019
Federated Learning: Challenges, Methods, and Future Directions Tian Li Anit Kumar Sahu Ameet Talwalkar Virginia Smith FedML 140 4,555 0 21 Aug 2019
Robust and Communication-Efficient Federated Learning from Non-IID Data Felix Sattler Simon Wiedemann K. Müller Wojciech Samek FedML 79 1,364 0 07 Mar 2019
Expanding the Reach of Federated Learning by Reducing Client Resource Requirements S. Caldas Jakub Konecný H. B. McMahan Ameet Talwalkar 98 450 0 18 Dec 2018
Federated Optimization in Heterogeneous Networks Tian Li Anit Kumar Sahu Manzil Zaheer Maziar Sanjabi Ameet Talwalkar Virginia Smith FedML 192 5,247 0 14 Dec 2018
Knowledge Distillation by On-the-Fly Native Ensemble Xu Lan Xiatian Zhu S. Gong 298 480 0 12 Jun 2018
Deep Gradient Compression: Reducing the Communication Bandwidth for Distributed Training Chengyue Wu Song Han Huizi Mao Yu Wang W. Dally 155 1,410 0 05 Dec 2017
Communication-Efficient Learning of Deep Networks from Decentralized Data H. B. McMahan Eider Moore Daniel Ramage S. Hampson Blaise Agüera y Arcas FedML 414 17,653 0 17 Feb 2016
Distilling the Knowledge in a Neural Network Geoffrey E. Hinton Oriol Vinyals J. Dean FedML 367 19,764 0 09 Mar 2015

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