Yu Inatsu

45 papers A* 6A 4Journal 35
YearRankTypeTitle / Venue / Authors
2025 J jnl
Bayesian Optimization of Robustness Measures Using Randomized GP-UCB-based Algorithms under Input Uncertainty.
CoRR
Yu Inatsu
2025 J jnl
Bayesian Optimization of Robustness Measures under Input Uncertainty: A Randomized Gaussian Process Upper Confidence Bound Approach.
Trans. Mach. Learn. Res.
Yu Inatsu
2025 A* conf
Distributionally Robust Active Learning for Gaussian Process Regression.
ICML
Shion Takeno, Yoshito Okura, Yu Inatsu, Tatsuya Aoyama, Tomonari Tanaka, Satoshi Akahane, Hiroyuki Hanada, Noriaki Hashimoto, Taro Murayama, Hanju Lee, Shinya Kojima, Ichiro Takeuchi
2025 J jnl
Distributionally Robust Active Learning for Gaussian Process Regression.
CoRR
Shion Takeno, Yoshito Okura, Yu Inatsu, Tatsuya Aoyama, Tomonari Tanaka, Satoshi Akahane, Hiroyuki Hanada, Noriaki Hashimoto, Taro Murayama, Hanju Lee, Shinya Kojima, Ichiro Takeuchi
2025 J jnl
Distributionally Robust Coreset Selection under Covariate Shift.
CoRR
Tomonari Tanaka, Hiroyuki Hanada, Hanting Yang, Tatsuya Aoyama, Yu Inatsu, Satoshi Akahane, Yoshito Okura, Noriaki Hashimoto, Taro Murayama, Hanju Lee, Shinya Kojima, Ichiro Takeuchi
2025 J jnl
Distributionally Robust Coreset Selection under Covariate Shift.
Trans. Mach. Learn. Res.
Tomonari Tanaka, Hiroyuki Hanada, Hanting Yang, Tatsuya Aoyama, Yu Inatsu, Satoshi Akahane, Yoshito Okura, Noriaki Hashimoto, Taro Murayama, Hanju Lee, Shinya Kojima, Ichiro Takeuchi
2025 J jnl
Dose-finding design based on level set estimation in phase I cancer clinical trials.
CoRR
Keiichiro Seno, Kota Matsui, Shogo Iwazaki, Yu Inatsu, Shion Takeno, Shigeyuki Matsui
2025 J jnl
Generalized Kernel Inducing Points by Duality Gap for Dataset Distillation.
CoRR
Tatsuya Aoyama, Hanting Yang, Hiroyuki Hanada, Satoshi Akahane, Tomonari Tanaka, Yoshito Okura, Yu Inatsu, Noriaki Hashimoto, Taro Murayama, Hanju Lee, Shinya Kojima, Ichiro Takeuchi
2025 A conf
No-Regret Bayesian Optimization with Stochastic Observation Failures.
AISTATS
Shogo Iwazaki, Tomohiko Tanabe, Mitsuru Irie, Shion Takeno, Kota Matsui, Yu Inatsu
2025 J jnl
Regret Analysis for Randomized Gaussian Process Upper Confidence Bound.
J. Artif. Intell. Res.
Shion Takeno, Yu Inatsu, Masayuki Karasuyama
2025 J jnl
Regret Analysis of Posterior Sampling-Based Expected Improvement for Bayesian Optimization.
CoRR
Shion Takeno, Yu Inatsu, Masayuki Karasuyama, Ichiro Takeuchi
2025 J jnl
Regret Analysis of Posterior Sampling-Based Expected Improvement for Bayesian Optimization.
Trans. Mach. Learn. Res.
Shion Takeno, Yu Inatsu, Masayuki Karasuyama, Ichiro Takeuchi
2024 J jnl
Active Learning for Level Set Estimation Using Randomized Straddle Algorithms.
CoRR
Yu Inatsu, Shion Takeno, Kentaro Kutsukake, Ichiro Takeuchi
2024 J jnl
Active Learning for Level Set Estimation Using Randomized Straddle Algorithms.
Trans. Mach. Learn. Res.
Yu Inatsu, Shion Takeno, Kentaro Kutsukake, Ichiro Takeuchi
2024 A conf
Bounding Box-based Multi-objective Bayesian Optimization of Risk Measures under Input Uncertainty.
AISTATS
Yu Inatsu, Shion Takeno, Hiroyuki Hanada, Kazuki Iwata, Ichiro Takeuchi
2024 J jnl
Distributionally Robust Safe Sample Screening.
CoRR
Hiroyuki Hanada, Tatsuya Aoyama, Satoshi Akahane, Tomonari Tanaka, Yoshito Okura, Yu Inatsu, Noriaki Hashimoto, Shion Takeno, Taro Murayama, Hanju Lee, Shinya Kojima, Ichiro Takeuchi
2024 J jnl
Distributionally Robust Safe Screening.
CoRR
Hiroyuki Hanada, Satoshi Akahane, Tatsuya Aoyama, Tomonari Tanaka, Yoshito Okura, Yu Inatsu, Noriaki Hashimoto, Taro Murayama, Hanju Lee, Shinya Kojima, Ichiro Takeuchi
2024 A* conf
Posterior Sampling-Based Bayesian Optimization with Tighter Bayesian Regret Bounds.
ICML
Shion Takeno, Yu Inatsu, Masayuki Karasuyama, Ichiro Takeuchi
2024 J jnl
Regret Analysis for Randomized Gaussian Process Upper Confidence Bound.
CoRR
Shion Takeno, Yu Inatsu, Masayuki Karasuyama
2024 A conf
Risk Seeking Bayesian Optimization under Uncertainty for Obtaining Extremum.
AISTATS
Shogo Iwazaki, Tomohiko Tanabe, Mitsuru Irie, Shion Takeno, Yu Inatsu
2023 J jnl
Distributionally Robust Multi-objective Bayesian Optimization under Uncertain Environments.
CoRR
Yu Inatsu, Ichiro Takeuchi
2023 J jnl
Posterior Sampling-Based Bayesian Optimization with Tighter Bayesian Regret Bounds.
CoRR
Shion Takeno, Yu Inatsu, Masayuki Karasuyama, Ichiro Takeuchi
2023 J jnl
Randomized Gaussian Process Upper Confidence Bound with Tight Bayesian Regret Bounds.
CoRR
Shion Takeno, Yu Inatsu, Masayuki Karasuyama
2023 A* conf
Randomized Gaussian Process Upper Confidence Bound with Tighter Bayesian Regret Bounds.
ICML
Shion Takeno, Yu Inatsu, Masayuki Karasuyama
2022 J jnl
Bayesian Optimization for Cascade-Type Multistage Processes.
Neural Comput.
Shunya Kusakawa, Shion Takeno, Yu Inatsu, Kentaro Kutsukake, Shogo Iwazaki, Takashi Nakano, Toru Ujihara, Masayuki Karasuyama, Ichiro Takeuchi
2022 A* conf
Bayesian Optimization for Distributionally Robust Chance-constrained Problem.
ICML
Yu Inatsu, Shion Takeno, Masayuki Karasuyama, Ichiro Takeuchi
2022 J jnl
Bayesian Optimization for Distributionally Robust Chance-constrained Problem.
CoRR
Yu Inatsu, Shion Takeno, Masayuki Karasuyama, Ichiro Takeuchi
2021 A* conf
Active Learning for Distributionally Robust Level-Set Estimation.
ICML
Yu Inatsu, Shogo Iwazaki, Ichiro Takeuchi
2021 J jnl
Active learning for distributionally robust level-set estimation.
CoRR
Yu Inatsu, Shogo Iwazaki, Ichiro Takeuchi
2021 J jnl
Bayesian Optimization for Cascade-type Multi-stage Processes.
CoRR
Shunya Kusakawa, Shion Takeno, Yu Inatsu, Kentaro Kutsukake, Shogo Iwazaki, Takashi Nakano, Toru Ujihara, Masayuki Karasuyama, Ichiro Takeuchi
2021 J jnl
Bayesian Quadrature Optimization for Probability Threshold Robustness Measure.
Neural Comput.
Shogo Iwazaki, Yu Inatsu, Ichiro Takeuchi
2021 J jnl
Conditional Selective Inference for Robust Regression and Outlier Detection using Piecewise-Linear Homotopy Continuation.
CoRR
Toshiaki Tsukurimichi, Yu Inatsu, Vo Nguyen Le Duy, Ichiro Takeuchi
2021 A conf
Mean-Variance Analysis in Bayesian Optimization under Uncertainty.
AISTATS
Shogo Iwazaki, Yu Inatsu, Ichiro Takeuchi
2021 J jnl
Valid and Exact Statistical Inference for Multi-dimensional Multiple Change-Points by Selective Inference.
CoRR
Ryota Sugiyama, Hiroki Toda, Vo Nguyen Le Duy, Yu Inatsu, Ichiro Takeuchi
2020 J jnl
Active Learning for Enumerating Local Minima Based on Gaussian Process Derivatives.
Neural Comput.
Yu Inatsu, Daisuke Sugita, Kazuaki Toyoura, Ichiro Takeuchi
2020 J jnl
Active Learning for Level Set Estimation Under Input Uncertainty and Its Extensions.
Neural Comput.
Yu Inatsu, Masayuki Karasuyama, Keiichi Inoue, Ichiro Takeuchi
2020 J jnl
Active Learning of Bayesian Linear Models with High-Dimensional Binary Features by Parameter Confidence-Region Estimation.
Neural Comput.
Yu Inatsu, Masayuki Karasuyama, Keiichi Inoue, Hideki Kandori, Ichiro Takeuchi
2020 J jnl
Bayesian Experimental Design for Finding Reliable Level Set Under Input Uncertainty.
IEEE Access
Shogo Iwazaki, Yu Inatsu, Ichiro Takeuchi
2020 J jnl
Bayesian Quadrature Optimization for Probability Threshold Robustness Measure.
CoRR
Shogo Iwazaki, Yu Inatsu, Ichiro Takeuchi
2020 A* conf
Computing Valid P-Values for Image Segmentation by Selective Inference.
CVPR
Kosuke Tanizaki, Noriaki Hashimoto, Yu Inatsu, Hidekata Hontani, Ichiro Takeuchi
2020 J jnl
Mean-Variance Analysis in Bayesian Optimization under Uncertainty.
CoRR
Shogo Iwazaki, Yu Inatsu, Ichiro Takeuchi
2019 J jnl
Active learning for enumerating local minima based on Gaussian process derivatives.
CoRR
Yu Inatsu, Daisuke Sugita, Kazuaki Toyoura, Ichiro Takeuchi
2019 J jnl
Active learning for level set estimation under cost-dependent input uncertainty.
CoRR
Yu Inatsu, Masayuki Karasuyama, Keiichi Inoue, Ichiro Takeuchi
2019 J jnl
Bayesian Experimental Design for Finding Reliable Level Set under Input Uncertainty.
CoRR
Shogo Iwazaki, Yu Inatsu, Ichiro Takeuchi
2019 J jnl
Computing Valid p-values for Image Segmentation by Selective Inference.
CoRR
Kosuke Tanizaki, Noriaki Hashimoto, Yu Inatsu, Hidekata Hontani, Ichiro Takeuchi