A thesis that packages the author's published federated learning work, whose main new theoretical result is an improved complexity bound for error-feedback compression.
InProceedings of the 2020 USENIX Annual Technical Con- ference, USENIX ATC 2020, July 15-17, 2020, Ada Gavrilovska and Erez Zadok (Eds.)
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Optimization Methods and Software for Federated Learning
A thesis that packages the author's published federated learning work, whose main new theoretical result is an improved complexity bound for error-feedback compression.