2 papers
cs.LG2023
On the Parallel Complexity of Multilevel Monte Carlo in Stochastic Gradient Descent
Kei Ishikawa
In the stochastic gradient descent (SGD) for sequential simulations such as the neural stochastic differential equations, the Multilevel Monte Carlo (MLMC) method is known to offer…
stat.ML2023
A Convex Framework for Confounding Robust Inference
Kei Ishikawa, Niao He, Takafumi Kanamori
We study policy evaluation of offline contextual bandits subject to unobserved confounders. Sensitivity analysis methods are commonly used to estimate the policy value under the wo…