Aaron's research focuses on improving the practice of machine learning through the development of more reliable and theoretically sound methods such as performance optimization, initialization, and normalization. He also drives current research frontiers in applied areas and is currently involved in MRI imaging reconstruction and automated theorem proving.
November 13, 2023
November 13, 2023
June 13, 2023
Aaron Defazio, Konstantin Mishchenko
June 13, 2023
May 13, 2022
May 13, 2022
October 14, 2021
Aaron Defazio, Robert Gower
October 14, 2021
November 18, 2019
November 18, 2019
November 18, 2019
November 18, 2019
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