Shion Takeno

According to our database, Shion Takeno authored at least 31 papers between 2019 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

Safe Distributionally Robust Feature Selection under Covariate Shift.

Hiroyuki Hanada, Satoshi Akahane, Noriaki Hashimoto, Shion Takeno, Ichiro Takeuchi

CoRR, March, 2026

On Regret Bounds of Thompson Sampling for Bayesian Optimization.

Shion Takeno, Shogo Iwazaki

CoRR, March, 2026

Randomized Kriging Believer for Parallel Bayesian Optimization with Regret Bounds.

Shuhei Sugiura, Ichiro Takeuchi, Shion Takeno

CoRR, March, 2026

2025

Dose-finding design based on level set estimation in phase I cancer clinical trials.

Keiichiro Seno, Kota Matsui, Shogo Iwazaki, Yu Inatsu, Shion Takeno, Shigeyuki Matsui

CoRR, April, 2025

Regret Analysis of Posterior Sampling-Based Expected Improvement for Bayesian Optimization.

Shion Takeno, Yu Inatsu, Masayuki Karasuyama, Ichiro Takeuchi

Trans. Mach. Learn. Res., 2025

Regret Analysis for Randomized Gaussian Process Upper Confidence Bound.

Shion Takeno, Yu Inatsu, Masayuki Karasuyama

J. Artif. Intell. Res., 2025

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

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Improved Regret Analysis in Gaussian Process Bandits: Optimality for Noiseless Reward, RKHS norm, and Non-Stationary Variance.

Shogo Iwazaki, Shion Takeno

Proceedings of the Forty-second International Conference on Machine Learning, 2025

No-Regret Bayesian Optimization with Stochastic Observation Failures.

Shogo Iwazaki, Tomohiko Tanabe, Mitsuru Irie, Shion Takeno, Kota Matsui, Yu Inatsu

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2025

Near-Optimal Algorithm for Non-Stationary Kernelized Bandits.

Shogo Iwazaki, Shion Takeno

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2025

2024

Active Learning for Level Set Estimation Using Randomized Straddle Algorithms.

Yu Inatsu, Shion Takeno, Kentaro Kutsukake, Ichiro Takeuchi

Trans. Mach. Learn. Res., 2024

Distributionally Robust Safe Sample Screening.

Hiroyuki Hanada, Tatsuya Aoyama, Satoshi Akahane, Tomonari Tanaka, Yoshito Okura, Yu Inatsu, Noriaki Hashimoto, Shion Takeno, Taro Murayama, Hanju Lee, Shinya Kojima, Ichiro Takeuchi

CoRR, 2024

Posterior Sampling-Based Bayesian Optimization with Tighter Bayesian Regret Bounds.

Shion Takeno, Yu Inatsu, Masayuki Karasuyama, Ichiro Takeuchi

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Hot off the Press: Towards Practical Preferential Bayesian Optimization with Skew Gaussian Processes.

Shion Takeno, Masahiro Nomura, Masayuki Karasuyama

Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2024

Risk Seeking Bayesian Optimization under Uncertainty for Obtaining Extremum.

Shogo Iwazaki, Tomohiko Tanabe, Mitsuru Irie, Shion Takeno, Yu Inatsu

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

Bounding Box-based Multi-objective Bayesian Optimization of Risk Measures under Input Uncertainty.

Yu Inatsu, Shion Takeno, Hiroyuki Hanada, Kazuki Iwata, Ichiro Takeuchi

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

Multi-Objective Bayesian Optimization with Active Preference Learning.

Ryota Ozaki, Kazuki Ishikawa, Youhei Kanzaki, Shion Takeno, Ichiro Takeuchi, Masayuki Karasuyama

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Multi-Objective Bayesian Optimization with Active Preference Learning.

Ryota Ozaki, Kazuki Ishikawa, Youhei Kanzaki, Shinya Suzuki, Shion Takeno, Ichiro Takeuchi, Masayuki Karasuyama

CoRR, 2023

Randomized Gaussian Process Upper Confidence Bound with Tight Bayesian Regret Bounds.

Shion Takeno, Yu Inatsu, Masayuki Karasuyama

CoRR, 2023

Failure-Aware Gaussian Process Optimization with Regret Bounds.

Shogo Iwazaki, Shion Takeno, Tomohiko Tanabe, Mitsuru Irie

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Towards Practical Preferential Bayesian Optimization with Skew Gaussian Processes.

Shion Takeno, Masahiro Nomura, Masayuki Karasuyama

Proceedings of the International Conference on Machine Learning, 2023

Randomized Gaussian Process Upper Confidence Bound with Tighter Bayesian Regret Bounds.

Shion Takeno, Yu Inatsu, Masayuki Karasuyama

Proceedings of the International Conference on Machine Learning, 2023

2022

A Generalized Framework of Multifidelity Max-Value Entropy Search Through Joint Entropy.

Shion Takeno, Hitoshi Fukuoka, Yuhki Tsukada, Toshiyuki Koyama, Motoki Shiga, Ichiro Takeuchi, Masayuki Karasuyama

Neural Comput., 2022

Bayesian Optimization for Cascade-Type Multistage Processes.

Shunya Kusakawa, Shion Takeno, Yu Inatsu, Kentaro Kutsukake, Shogo Iwazaki, Takashi Nakano, Toru Ujihara, Masayuki Karasuyama, Ichiro Takeuchi

Neural Comput., 2022

Sequential and Parallel Constrained Max-value Entropy Search via Information Lower Bound.

Shion Takeno, Tomoyuki Tamura, Kazuki Shitara, Masayuki Karasuyama

Proceedings of the International Conference on Machine Learning, 2022

Bayesian Optimization for Distributionally Robust Chance-constrained Problem.

Yu Inatsu, Shion Takeno, Masayuki Karasuyama, Ichiro Takeuchi

Proceedings of the International Conference on Machine Learning, 2022

2021

Bayesian Optimization for Cascade-type Multi-stage Processes.

Shunya Kusakawa, Shion Takeno, Yu Inatsu, Kentaro Kutsukake, Shogo Iwazaki, Takashi Nakano, Toru Ujihara, Masayuki Karasuyama, Ichiro Takeuchi

CoRR, 2021

2020

Cost-effective search for lower-error region in material parameter space using multifidelity Gaussian process modeling.

Shion Takeno, Yuhki Tsukada, Hitoshi Fukuoka, Toshiyuki Koyama, Motoki Shiga, Masayuki Karasuyama

CoRR, 2020

Multi-fidelity Bayesian Optimization with Max-value Entropy Search and its Parallelization.

Shion Takeno, Hitoshi Fukuoka, Yuhki Tsukada, Toshiyuki Koyama, Motoki Shiga, Ichiro Takeuchi, Masayuki Karasuyama

Proceedings of the 37th International Conference on Machine Learning, 2020

Multi-objective Bayesian Optimization using Pareto-frontier Entropy.

Shinya Suzuki, Shion Takeno, Tomoyuki Tamura, Kazuki Shitara, Masayuki Karasuyama

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Multi-fidelity Bayesian Optimization with Max-value Entropy Search.

Shion Takeno, Hitoshi Fukuoka, Yuhki Tsukada, Toshiyuki Koyama, Motoki Shiga, Ichiro Takeuchi, Masayuki Karasuyama

CoRR, 2019