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Yu Inatsu
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2020 – today
- 2024
- [c8]Shogo Iwazaki, Tomohiko Tanabe, Mitsuru Irie, Shion Takeno, Yu Inatsu:
Risk Seeking Bayesian Optimization under Uncertainty for Obtaining Extremum. AISTATS 2024: 1252-1260 - [c7]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: 4564-4572 - [c6]Shion Takeno, Yu Inatsu, Masayuki Karasuyama, Ichiro Takeuchi:
Posterior Sampling-Based Bayesian Optimization with Tighter Bayesian Regret Bounds. ICML 2024 - [i18]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 abs/2404.16328 (2024) - [i17]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 abs/2406.05964 (2024) - [i16]Yu Inatsu, Shion Takeno, Kentaro Kutsukake, Ichiro Takeuchi:
Active Learning for Level Set Estimation Using Randomized Straddle Algorithms. CoRR abs/2408.03144 (2024) - [i15]Shion Takeno, Yu Inatsu, Masayuki Karasuyama:
Regret Analysis for Randomized Gaussian Process Upper Confidence Bound. CoRR abs/2409.00979 (2024) - 2023
- [c5]Shion Takeno, Yu Inatsu, Masayuki Karasuyama:
Randomized Gaussian Process Upper Confidence Bound with Tighter Bayesian Regret Bounds. ICML 2023: 33490-33515 - [i14]Yu Inatsu, Ichiro Takeuchi:
Distributionally Robust Multi-objective Bayesian Optimization under Uncertain Environments. CoRR abs/2301.11588 (2023) - [i13]Shion Takeno, Yu Inatsu, Masayuki Karasuyama:
Randomized Gaussian Process Upper Confidence Bound with Tight Bayesian Regret Bounds. CoRR abs/2302.01511 (2023) - [i12]Shion Takeno, Yu Inatsu, Masayuki Karasuyama, Ichiro Takeuchi:
Posterior Sampling-Based Bayesian Optimization with Tighter Bayesian Regret Bounds. CoRR abs/2311.03760 (2023) - 2022
- [j6]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): 2408-2431 (2022) - [c4]Yu Inatsu, Shion Takeno, Masayuki Karasuyama, Ichiro Takeuchi:
Bayesian Optimization for Distributionally Robust Chance-constrained Problem. ICML 2022: 9602-9621 - [i11]Yu Inatsu, Shion Takeno, Masayuki Karasuyama, Ichiro Takeuchi:
Bayesian Optimization for Distributionally Robust Chance-constrained Problem. CoRR abs/2201.13112 (2022) - 2021
- [j5]Shogo Iwazaki, Yu Inatsu, Ichiro Takeuchi:
Bayesian Quadrature Optimization for Probability Threshold Robustness Measure. Neural Comput. 33(12): 3413-3466 (2021) - [c3]Shogo Iwazaki, Yu Inatsu, Ichiro Takeuchi:
Mean-Variance Analysis in Bayesian Optimization under Uncertainty. AISTATS 2021: 973-981 - [c2]Yu Inatsu, Shogo Iwazaki, Ichiro Takeuchi:
Active Learning for Distributionally Robust Level-Set Estimation. ICML 2021: 4574-4584 - [i10]Yu Inatsu, Shogo Iwazaki, Ichiro Takeuchi:
Active learning for distributionally robust level-set estimation. CoRR abs/2102.04000 (2021) - [i9]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 abs/2104.10840 (2021) - [i8]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 abs/2110.08989 (2021) - [i7]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 abs/2111.08330 (2021) - 2020
- [j4]Shogo Iwazaki, Yu Inatsu
, Ichiro Takeuchi
Bayesian Experimental Design for Finding Reliable Level Set Under Input Uncertainty. IEEE Access 8: 203982-203993 (2020) - [j3]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): 1998-2031 (2020) - [j2]Yu Inatsu, Daisuke Sugita, Kazuaki Toyoura, Ichiro Takeuchi:
Active Learning for Enumerating Local Minima Based on Gaussian Process Derivatives. Neural Comput. 32(10): 2032-2068 (2020) - [j1]Yu Inatsu, Masayuki Karasuyama, Keiichi Inoue, Ichiro Takeuchi:
Active Learning for Level Set Estimation Under Input Uncertainty and Its Extensions. Neural Comput. 32(12): 2486-2531 (2020) - [c1]Kosuke Tanizaki, Noriaki Hashimoto, Yu Inatsu, Hidekata Hontani, Ichiro Takeuchi:
Computing Valid P-Values for Image Segmentation by Selective Inference. CVPR 2020: 9550-9559 - [i6]Shogo Iwazaki, Yu Inatsu, Ichiro Takeuchi:
Bayesian Quadrature Optimization for Probability Threshold Robustness Measure. CoRR abs/2006.11986 (2020) - [i5]Shogo Iwazaki, Yu Inatsu, Ichiro Takeuchi:
Mean-Variance Analysis in Bayesian Optimization under Uncertainty. CoRR abs/2009.08166 (2020)
2010 – 2019
- 2019
- [i4]Yu Inatsu, Daisuke Sugita, Kazuaki Toyoura, Ichiro Takeuchi:
Active learning for enumerating local minima based on Gaussian process derivatives. CoRR abs/1903.03279 (2019) - [i3]Kosuke Tanizaki, Noriaki Hashimoto, Yu Inatsu, Hidekata Hontani, Ichiro Takeuchi:
Computing Valid p-values for Image Segmentation by Selective Inference. CoRR abs/1906.00629 (2019) - [i2]Yu Inatsu, Masayuki Karasuyama, Keiichi Inoue, Ichiro Takeuchi:
Active learning for level set estimation under cost-dependent input uncertainty. CoRR abs/1909.06064 (2019) - [i1]Shogo Iwazaki, Yu Inatsu, Ichiro Takeuchi:
Bayesian Experimental Design for Finding Reliable Level Set under Input Uncertainty. CoRR abs/1910.12043 (2019)
Coauthor Index
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