Acceleration for compressed gradient descent in distributed and federated optimization

Due to the high communication cost in distributed and federated learning problems, methods relying on compression of communicated messages are becoming increasingly popular. While in other contexts the best performing gradient-type methods invariably rely on some form of acceleration/momentum to red...

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Bibliographic Details
Main Authors: LI, Zhize, KOVALEV, Dmitry, QIAN, Xun, RICHTARIK, Peter
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2020
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Online Access:https://ink.library.smu.edu.sg/sis_research/8681
https://ink.library.smu.edu.sg/context/sis_research/article/9684/viewcontent/ICML20_full_adiana.pdf
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Institution: Singapore Management University
Language: English