| 2025 | AISTATS | No-Regret Bayesian Optimization with Stochastic Observation Failures. | Shogo Iwazaki, Tomohiko Tanabe, Mitsuru Irie, Shion Takeno, Kota Matsui, Yu Inatsu |
| 2025 | ICML | Distributionally Robust Active Learning for Gaussian Process Regression. | Shion Takeno, Yoshito Okura, Yu Inatsu, Tatsuya Aoyama, Tomonari Tanaka, Satoshi Akahane, Hiroyuki Hanada, Noriaki Hashimoto, Taro Murayama, Hanju Lee, Shinya Kojima, Ichiro Takeuchi |
| 2024 | AISTATS | Bounding Box-based Multi-objective Bayesian Optimization of Risk Measures under Input Uncertainty. | Yu Inatsu, Shion Takeno, Hiroyuki Hanada, Kazuki Iwata, Ichiro Takeuchi |
| 2024 | AISTATS | Risk Seeking Bayesian Optimization under Uncertainty for Obtaining Extremum. | Shogo Iwazaki, Tomohiko Tanabe, Mitsuru Irie, Shion Takeno, Yu Inatsu |
| 2024 | ICML | Posterior Sampling-Based Bayesian Optimization with Tighter Bayesian Regret Bounds. | Shion Takeno, Yu Inatsu, Masayuki Karasuyama, Ichiro Takeuchi |
| 2023 | ICML | Randomized Gaussian Process Upper Confidence Bound with Tighter Bayesian Regret Bounds. | Shion Takeno, Yu Inatsu, Masayuki Karasuyama |
| 2022 | ICML | Bayesian Optimization for Distributionally Robust Chance-constrained Problem. | Yu Inatsu, Shion Takeno, Masayuki Karasuyama, Ichiro Takeuchi |
| 2021 | AISTATS | Mean-Variance Analysis in Bayesian Optimization under Uncertainty. | Shogo Iwazaki, Yu Inatsu, Ichiro Takeuchi |
| 2021 | ICML | Active Learning for Distributionally Robust Level-Set Estimation. | Yu Inatsu, Shogo Iwazaki, Ichiro Takeuchi |
| 2020 | CVPR | Computing Valid P-Values for Image Segmentation by Selective Inference. | Kosuke Tanizaki, Noriaki Hashimoto, Yu Inatsu, Hidekata Hontani, Ichiro Takeuchi |