no code implementations • 20 Mar 2023 • Keigo Habara, Ellen Hidemi Fukuda, Nobuo Yamashita
It can represent games with multiple decision points and incomplete information, and hence it is helpful in formulating games with uncertain inputs, such as poker.
no code implementations • 23 Aug 2022 • Hardik Tankaria, Nobuo Yamashita
In this paper, we consider to improve the stochastic variance reduce gradient (SVRG) method via incorporating the curvature information of the objective function.
1 code implementation • 11 May 2022 • Hiroki Tanabe, Ellen H. Fukuda, Nobuo Yamashita
Convex-composite optimization, which minimizes an objective function represented by the sum of a differentiable function and a convex one, is widely used in machine learning and signal/image processing.
