Q-SHED: Distributed Optimization at the Edge via Hessian Eigenvectors Quantization
Author:
Affiliation:
1. University of Padova,Department of Information Engineering,Padova,Italy
2. Uppsala University,Department of Electrical Engineering,Uppsala,Sweden
Funder
European Union
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10278505/10278554/10279510.pdf?arnumber=10279510
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4. LIBSVM
5. FedNL: Making Newton-type methods applicable to federated learning;safaryan;Proceedings of the 39th International Conference on Machine Learning,0
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