Kohei Miyaguchi

31 papers A* 8A 2B 2Journal 17Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Inference-Aware Meta-Alignment of LLMs via Non-Linear GRPO. CoRR Shokichi Takakura, Akifumi Wachi, Rei Higuchi, Kohei Miyaguchi, Taiji Suzuki
2025	J	`jnl`	A Provable Approach for End-to-End Safe Reinforcement Learning. CoRR Akifumi Wachi, Kohei Miyaguchi, Takumi Tanabe, Rei Sato, Youhei Akimoto
2025	J	`jnl`	Cross-Process Defect Attribution using Potential Loss Analysis. CoRR Tsuyoshi Idé, Kohei Miyaguchi
2025	J	`jnl`	Path Learning with Trajectory Advantage Regression. CoRR Kohei Miyaguchi
2025	J	`jnl`	Sequence-Aware Inline Measurement Attribution for Good-Bad Wafer Diagnosis. CoRR Kohei Miyaguchi, Masao Joko, Rebekah Sheraw, Tsuyoshi Idé
2025	J	`jnl`	Wafer Defect Root Cause Analysis with Partial Trajectory Regression. CoRR Kohei Miyaguchi, Masao Joko, Rebekah Sheraw, Tsuyoshi Idé
2024	J	`jnl`	Detection of Unobserved Common Causes based on NML Code in Discrete, Mixed, and Continuous Variables. CoRR Masatoshi Kobayashi, Kohei Miyaguchi, Shin Matsushima
2024	J	`jnl`	Socially efficient mechanism on the minimum budget. CoRR Hirota Kinoshita, Takayuki Osogami, Kohei Miyaguchi
2024	A*	`conf`	Worst-Case Offline Reinforcement Learning with Arbitrary Data Support. NeurIPS Kohei Miyaguchi
2023	A*	`conf`	Biases in Evaluation of Molecular Optimization Methods and Bias Reduction Strategies. ICML Hiroshi Kajino, Kohei Miyaguchi, Takayuki Osogami
2022	J	`jnl`	A Theoretical Framework of Almost Hyperparameter-free Hyperparameter Selection Methods for Offline Policy Evaluation. CoRR Kohei Miyaguchi
2022	J	`jnl`	Biases in In Silico Evaluation of Molecular Optimization Methods and Bias-Reduced Evaluation Methodology. CoRR Hiroshi Kajino, Kohei Miyaguchi, Takayuki Osogami
2022	A*	`conf`	Cumulative Stay-time Representation for Electronic Health Records in Medical Event Time Prediction. IJCAI Takayuki Katsuki, Kohei Miyaguchi, Akira Koseki, Toshiya Iwamori, Ryosuke Yanagiya, Atsushi Suzuki
2022	J	`jnl`	Cumulative Stay-time Representation for Electronic Health Records in Medical Event Time Prediction. CoRR Takayuki Katsuki, Kohei Miyaguchi, Akira Koseki, Toshiya Iwamori, Ryosuke Yanagiya, Atsushi Suzuki
2022	B	`conf`	Detection of Unobserved Common Cause in Discrete Data Based on the MDL Principle. IEEE Big Data Masatoshi Kobayashi, Kohei Miyaguchi, Shin Matsushima
2022	A*	`conf`	Hierarchical Lattice Layer for Partially Monotone Neural Networks. NeurIPS Hiroki Yanagisawa, Kohei Miyaguchi, Takayuki Katsuki
2022	A*	`conf`	Variational Inference for Discriminative Learning with Generative Modeling of Feature Incompletion. ICLR Kohei Miyaguchi, Takayuki Katsuki, Akira Koseki, Toshiya Iwamori
2021	A*	`conf`	Asymptotically Exact Error Characterization of Offline Policy Evaluation with Misspecified Linear Models. NeurIPS Kohei Miyaguchi
2019	A	`conf`	Adaptive Minimax Regret against Smooth Logarithmic Losses over High-Dimensional l1-Balls via Envelope Complexity. AISTATS Kohei Miyaguchi, Kenji Yamanishi
2019	A*	`conf`	Cogra: Concept-Drift-Aware Stochastic Gradient Descent for Time-Series Forecasting. AAAI Kohei Miyaguchi, Hiroshi Kajino
2019	J	`jnl`	PAC-Bayesian Transportation Bound. CoRR Kohei Miyaguchi
2018	J	`jnl`	Adaptive Minimax Regret against Smooth Logarithmic Losses over High-Dimensional ε CoRR Kohei Miyaguchi, Kenji Yamanishi
2018	J	`jnl`	High-dimensional Penalty Selection via Minimum Description Length Principle. CoRR Kohei Miyaguchi, Kenji Yamanishi
2018	J	`jnl`	High-dimensional penalty selection via minimum description length principle. Mach. Learn. Kohei Miyaguchi, Kenji Yamanishi
2017	—	`conf`	Detecting changes in streaming data with information-theoretic windowing. IEEE BigData Ryoya Kaneko, Kohei Miyaguchi, Kenji Yamanishi
2017	J	`jnl`	Normalized Maximum Likelihood with Luckiness for Multivariate Normal Distributions. CoRR Kohei Miyaguchi
2017	J	`jnl`	Online detection of continuous changes in stochastic processes. Int. J. Data Sci. Anal. Kohei Miyaguchi, Kenji Yamanishi
2017	A	`conf`	Sparse Graphical Modeling via Stochastic Complexity. SDM Kohei Miyaguchi, Shin Matsushima, Kenji Yamanishi
2016	—	`conf`	Detecting gradual changes from data stream using MDL-change statistics. IEEE BigData Kenji Yamanishi, Kohei Miyaguchi
2016	A*	`conf`	Structure Selection for Convolutive Non-negative Matrix Factorization Using Normalized Maximum Likelihood Coding. ICDM Atsushi Suzuki, Kohei Miyaguchi, Kenji Yamanishi
2015	B	`conf`	On-line detection of continuous changes in stochastic processes. DSAA Kohei Miyaguchi, Kenji Yamanishi