MARINA: Faster non-convex distributed learning with compression

We develop and analyze MARINA: a new communication efficient method for non-convex distributed learning over heterogeneous datasets. MARINA employs a novel communication compression strategy based on the compression of gradient differences that is reminiscent of but different from the strategy emplo...

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Bibliographic Details
Main Authors: GORBUNOV, Eduard, BURLACHENKO, Konstantin, LI, Zhize, RICHTARIK, Peter
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2021
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Online Access:https://ink.library.smu.edu.sg/sis_research/8682
https://ink.library.smu.edu.sg/context/sis_research/article/9685/viewcontent/ICML21_full_marina.pdf
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Institution: Singapore Management University
Language: English