Yu Inatsu

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 29

Top Topics

Gaussian Process

Robust Optimization

Active Learning

Top Venues

Publications

Yu Inatsu, Shion Takeno, Hiroyuki Hanada, Kazuki Iwata, Ichiro Takeuchi
Bounding Box-based Multi-objective Bayesian Optimization of Risk Measures under Input Uncertainty. AISTATS (2024)
Shogo Iwazaki, Tomohiko Tanabe, Mitsuru Irie, Shion Takeno, Yu Inatsu
Risk Seeking Bayesian Optimization under Uncertainty for Obtaining Extremum. AISTATS (2024)
Hiroyuki Hanada, Satoshi Akahane, Tatsuya Aoyama, Tomonari Tanaka, Yoshito Okura, Yu Inatsu, Noriaki Hashimoto, Taro Murayama, Lee Hanju, Shinya Kojima, Ichiro Takeuchi
Distributionally Robust Safe Screening. CoRR (2024)
Hiroyuki Hanada, Tatsuya Aoyama, Satoshi Akahane, Tomonari Tanaka, Yoshito Okura, Yu Inatsu, Noriaki Hashimoto, Shion Takeno, Taro Murayama, Lee Hanju, Shinya Kojima, Ichiro Takeuchi
Distributionally Robust Safe Sample Screening. CoRR (2024)
Shion Takeno, Yu Inatsu, Masayuki Karasuyama
Randomized Gaussian Process Upper Confidence Bound with Tighter Bayesian Regret Bounds. ICML (2023)
Shion Takeno, Yu Inatsu, Masayuki Karasuyama, Ichiro Takeuchi
Posterior Sampling-Based Bayesian Optimization with Tighter Bayesian Regret Bounds. CoRR (2023)
Shion Takeno, Yu Inatsu, Masayuki Karasuyama
Randomized Gaussian Process Upper Confidence Bound with Tight Bayesian Regret Bounds. CoRR (2023)
Yu Inatsu, Ichiro Takeuchi
Distributionally Robust Multi-objective Bayesian Optimization under Uncertain Environments. CoRR (2023)
Yu Inatsu, Shion Takeno, Masayuki Karasuyama, Ichiro Takeuchi
Bayesian Optimization for Distributionally Robust Chance-constrained Problem. CoRR (2022)
Yu Inatsu, Shion Takeno, Masayuki Karasuyama, Ichiro Takeuchi
Bayesian Optimization for Distributionally Robust Chance-constrained Problem. ICML (2022)
Shunya Kusakawa, Shion Takeno, Yu Inatsu, Kentaro Kutsukake, Shogo Iwazaki, Takashi Nakano, Toru Ujihara, Masayuki Karasuyama, Ichiro Takeuchi
Bayesian Optimization for Cascade-Type Multistage Processes. Neural Comput. 34 (12) (2022)
Shogo Iwazaki, Yu Inatsu, Ichiro Takeuchi
Bayesian Quadrature Optimization for Probability Threshold Robustness Measure. Neural Comput. 33 (12) (2021)
Toshiaki Tsukurimichi, Yu Inatsu, Vo Nguyen Le Duy, Ichiro Takeuchi
Conditional Selective Inference for Robust Regression and Outlier Detection using Piecewise-Linear Homotopy Continuation. CoRR (2021)
Ryota Sugiyama, Hiroki Toda, Vo Nguyen Le Duy, Yu Inatsu, Ichiro Takeuchi
Valid and Exact Statistical Inference for Multi-dimensional Multiple Change-Points by Selective Inference. CoRR (2021)
Yu Inatsu, Shogo Iwazaki, Ichiro Takeuchi
Active learning for distributionally robust level-set estimation. CoRR (2021)
Yu Inatsu, Shogo Iwazaki, Ichiro Takeuchi
Active Learning for Distributionally Robust Level-Set Estimation. ICML (2021)
Shogo Iwazaki, Yu Inatsu, Ichiro Takeuchi
Mean-Variance Analysis in Bayesian Optimization under Uncertainty. AISTATS (2021)
Shunya Kusakawa, Shion Takeno, Yu Inatsu, Kentaro Kutsukake, Shogo Iwazaki, Takashi Nakano, Toru Ujihara, Masayuki Karasuyama, Ichiro Takeuchi
Bayesian Optimization for Cascade-type Multi-stage Processes. CoRR (2021)
Shogo Iwazaki, Yu Inatsu, Ichiro Takeuchi
Bayesian Experimental Design for Finding Reliable Level Set Under Input Uncertainty. IEEE Access 8 (2020)
Shogo Iwazaki, Yu Inatsu, Ichiro Takeuchi
Mean-Variance Analysis in Bayesian Optimization under Uncertainty. CoRR (2020)
Yu Inatsu, Daisuke Sugita, Kazuaki Toyoura, Ichiro Takeuchi
Active Learning for Enumerating Local Minima Based on Gaussian Process Derivatives. Neural Comput. 32 (10) (2020)
Kosuke Tanizaki, Noriaki Hashimoto, Yu Inatsu, Hidekata Hontani, Ichiro Takeuchi
Computing Valid P-Values for Image Segmentation by Selective Inference. CVPR (2020)
Shogo Iwazaki, Yu Inatsu, Ichiro Takeuchi
Bayesian Quadrature Optimization for Probability Threshold Robustness Measure. CoRR (2020)
Yu Inatsu, Masayuki Karasuyama, Keiichi Inoue, Ichiro Takeuchi
Active Learning for Level Set Estimation Under Input Uncertainty and Its Extensions. Neural Comput. 32 (12) (2020)
Yu Inatsu, Masayuki Karasuyama, Keiichi Inoue, Hideki Kandori, Ichiro Takeuchi
Active Learning of Bayesian Linear Models with High-Dimensional Binary Features by Parameter Confidence-Region Estimation. Neural Comput. 32 (10) (2020)
Shogo Iwazaki, Yu Inatsu, Ichiro Takeuchi
Bayesian Experimental Design for Finding Reliable Level Set under Input Uncertainty. CoRR (2019)
Kosuke Tanizaki, Noriaki Hashimoto, Yu Inatsu, Hidekata Hontani, Ichiro Takeuchi
Computing Valid p-values for Image Segmentation by Selective Inference. CoRR (2019)
Yu Inatsu, Daisuke Sugita, Kazuaki Toyoura, Ichiro Takeuchi
Active learning for enumerating local minima based on Gaussian process derivatives. CoRR (2019)
Yu Inatsu, Masayuki Karasuyama, Keiichi Inoue, Ichiro Takeuchi
Active learning for level set estimation under cost-dependent input uncertainty. CoRR (2019)