FedGreen: Carbon-Aware Federated Learning with Model Size Adaptation

Author:

Abbasi Ali1,Dong Fan1,Wang Xin2,Leung Henry1,Zhou Jiayu3,Drew Steve1

Affiliation:

1. University of Calgary,Department of Electrical and Software Engineering,Calgary,AB,Canada

2. University of Calgary,Department of Geomatics Engineering,Calgary,AB,Canada

3. Michigan State University,Department of Computer Science and Engineering,East Lansing,MI,USA

Publisher

IEEE

Reference12 articles.

1. A review of the theoretical research and practical progress of carbon neutrality

2. A first look into the carbon foot-print of federated learning;Qiu;arXiv preprint,2021

3. Fjord: Fair and accurate federated learning under heterogeneous targets with ordered dropout;Horvath;Advances in Neural Information Processing Systems,2021

4. Communication-efficient learning of deep networks from decentralized data;McMahan;Artificial intelligence and statistics,2017

5. Heterofl: Computation and communication efficient federated learning for het-erogeneous clients;Diao;arXiv preprint,2020

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