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math.OC2026
Adaptive Gradient-Based Methods for a Broader Class of Optimization Problems under Performative Prediction
Hiroki Hamaguchi, Yuya Hikima, Hiroshi Sawada +1
We study optimization under performative prediction, where deploying a model affects the future data distribution. For this setting, several gradient-based approaches have been pro…
math.OC2025
Zeroth-order gradient estimators for stochastic problems with decision-dependent distributions
Yuya Hikima, Akiko Takeda
Stochastic optimization problems with unknown decision-dependent distributions have attracted increasing attention in recent years due to its importance in applications. Since the…
math.OC2024
Zeroth-Order Methods for Nonconvex Stochastic Problems with Decision-Dependent Distributions
Yuya Hikima, Akiko Takeda
In this study, we consider an optimization problem with uncertainty dependent on decision variables, which has recently attracted attention due to its importance in machine learnin…