Miyaguchi, Kohei

10 publications

NeurIPS 2025 A Provable Approach for End-to-End Safe Reinforcement Learning Akifumi Wachi, Kohei Miyaguchi, Takumi Tanabe, Rei Sato, Youhei Akimoto

NeurIPS 2024 Worst-Case Offline Reinforcement Learning with Arbitrary Data Support Kohei Miyaguchi

ICML 2023 Biases in Evaluation of Molecular Optimization Methods and Bias Reduction Strategies Hiroshi Kajino, Kohei Miyaguchi, Takayuki Osogami

IJCAI 2022 Cumulative Stay-Time Representation for Electronic Health Records in Medical Event Time Prediction Takayuki Katsuki, Kohei Miyaguchi, Akira Koseki, Toshiya Iwamori, Ryosuke Yanagiya, Atsushi Suzuki

NeurIPS 2022 Hierarchical Lattice Layer for Partially Monotone Neural Networks Hiroki Yanagisawa, Kohei Miyaguchi, Takayuki Katsuki

ICLR 2022 Variational Inference for Discriminative Learning with Generative Modeling of Feature Incompletion Kohei Miyaguchi, Takayuki Katsuki, Akira Koseki, Toshiya Iwamori

NeurIPS 2021 Asymptotically Exact Error Characterization of Offline Policy Evaluation with Misspecified Linear Models Kohei Miyaguchi

AISTATS 2019 Adaptive Minimax Regret Against Smooth Logarithmic Losses over High-Dimensional L1-Balls via Envelope Complexity Kohei Miyaguchi, Kenji Yamanishi

AAAI 2019 Cogra: Concept-Drift-Aware Stochastic Gradient Descent for Time-Series Forecasting Kohei Miyaguchi, Hiroshi Kajino

MLJ 2018 High-Dimensional Penalty Selection via Minimum Description Length Principle Kohei Miyaguchi, Kenji Yamanishi