Department of Mathematics

Applied Mathematics

  •  Zaiwen Wen, Peking University, China
  •  Stochastic Second-Order Methods For Deep Learning
  •  02/25/2021
  •  3:30 AM - 4:30 AM
  •  Online (virtual meeting) (Virtual Meeting Link)
  •  Olga Turanova (turanova@msu.edu)

Stochastic methods are widely used in deep learning. In this talk, we first review the state-of-the-art methods such as KFAC. Then we present a structured stochastic quasi-Newton method and a sketchy empirical natural gradient method. Numerical results on deep convolution networks illustrate that our methods are quite competitive to SGD and KFAC.

 

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Michigan State University
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