2 citations · 2 across the 1 of their papers we have counts for
2 papers
math.NA2022★ 2 cited
Constructing unbiased gradient estimators with finite variance for conditional stochastic optimization
Takashi Goda, Wataru Kitade
We study stochastic gradient descent for solving conditional stochastic optimization problems, in which an objective to be minimized is given by a parametric nested expectation wit…
stat.CO2020
Unbiased MLMC stochastic gradient-based optimization of Bayesian experimental designs
Takashi Goda, Tomohiko Hironaka, Wataru Kitade +1
In this paper we propose an efficient stochastic optimization algorithm to search for Bayesian experimental designs such that the expected information gain is maximized. The gradie…