Shogo Iwazaki - RankMe

26 papers A* 5A 4Journal 17

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	On Regret Bounds of Thompson Sampling for Bayesian Optimization. CoRR Shion Takeno, Shogo Iwazaki
2026	J	`jnl`	Tighter Regret Lower Bound for Gaussian Process Bandits with Squared Exponential Kernel in Hypersphere. CoRR Shogo Iwazaki
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`	Gaussian Process Upper Confidence Bound Achieves Nearly-Optimal Regret in Noise-Free Gaussian Process Bandits. CoRR Shogo Iwazaki
2025	J	`jnl`	High-dimensional Nonparametric Contextual Bandit Problem. CoRR Shogo Iwazaki, Junpei Komiyama, Masaaki Imaizumi
2025	A*	`conf`	Improved Regret Analysis in Gaussian Process Bandits: Optimality for Noiseless Reward, RKHS norm, and Non-Stationary Variance. ICML Shogo Iwazaki, Shion Takeno
2025	J	`jnl`	Improved Regret Analysis in Gaussian Process Bandits: Optimality for Noiseless Reward, RKHS norm, and Non-Stationary Variance. CoRR Shogo Iwazaki, Shion Takeno
2025	J	`jnl`	Improved Regret Bounds for Gaussian Process Upper Confidence Bound in Bayesian Optimization. CoRR Shogo Iwazaki
2025	A	`conf`	Near-Optimal Algorithm for Non-Stationary Kernelized Bandits. AISTATS Shogo Iwazaki, Shion Takeno
2025	A	`conf`	No-Regret Bayesian Optimization with Stochastic Observation Failures. AISTATS Shogo Iwazaki, Tomohiko Tanabe, Mitsuru Irie, Shion Takeno, Kota Matsui, Yu Inatsu
2024	J	`jnl`	Near-Optimal Algorithm for Non-Stationary Kernelized Bandits. CoRR Shogo Iwazaki, Shion Takeno
2024	A*	`conf`	No-Regret Bandit Exploration based on Soft Tree Ensemble Model. NeurIPS Shogo Iwazaki, Shinya Suzumura
2024	A	`conf`	Risk Seeking Bayesian Optimization under Uncertainty for Obtaining Extremum. AISTATS Shogo Iwazaki, Tomohiko Tanabe, Mitsuru Irie, Shion Takeno, Yu Inatsu
2023	A*	`conf`	Failure-Aware Gaussian Process Optimization with Regret Bounds. NeurIPS Shogo Iwazaki, Shion Takeno, Tomohiko Tanabe, Mitsuru Irie
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`	Quantifying Statistical Significance of Neural Network-based Image Segmentation by Selective Inference. NeurIPS Vo Nguyen Le Duy, Shogo Iwazaki, 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	A	`conf`	Mean-Variance Analysis in Bayesian Optimization under Uncertainty. AISTATS Shogo Iwazaki, Yu Inatsu, 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	J	`jnl`	Mean-Variance Analysis in Bayesian Optimization under Uncertainty. CoRR Shogo Iwazaki, Yu Inatsu, Ichiro Takeuchi
2020	J	`jnl`	Quantifying Statistical Significance of Neural Network Representation-Driven Hypotheses by Selective Inference. CoRR Vo Nguyen Le Duy, Shogo Iwazaki, Ichiro Takeuchi
2019	J	`jnl`	Bayesian Experimental Design for Finding Reliable Level Set under Input Uncertainty. CoRR Shogo Iwazaki, Yu Inatsu, Ichiro Takeuchi