Shogo Iwazaki

According to our database, Shogo Iwazaki authored at least 18 papers between 2020 and 2025.

Collaborative distances:

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

2025

Improved Regret Bounds for Gaussian Process Upper Confidence Bound in Bayesian Optimization.

Shogo Iwazaki

CoRR, June, 2025

High-dimensional Nonparametric Contextual Bandit Problem.

Shogo Iwazaki, Junpei Komiyama, Masaaki Imaizumi

CoRR, May, 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

Gaussian Process Upper Confidence Bound Achieves Nearly-Optimal Regret in Noise-Free Gaussian Process Bandits.

Shogo Iwazaki

CoRR, February, 2025

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

Shogo Iwazaki, Shion Takeno

CoRR, February, 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

No-Regret Bandit Exploration based on Soft Tree Ensemble Model.

Shogo Iwazaki, Shinya Suzumura

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 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

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

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

Quantifying Statistical Significance of Neural Network-based Image Segmentation by Selective Inference.

Vo Nguyen Le Duy, Shogo Iwazaki, Ichiro Takeuchi

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Bayesian Quadrature Optimization for Probability Threshold Robustness Measure.

Shogo Iwazaki, Yu Inatsu, Ichiro Takeuchi

Neural Comput., 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

Active Learning for Distributionally Robust Level-Set Estimation.

Yu Inatsu, Shogo Iwazaki, Ichiro Takeuchi

Proceedings of the 38th International Conference on Machine Learning, 2021

Mean-Variance Analysis in Bayesian Optimization under Uncertainty.

Shogo Iwazaki, Yu Inatsu, Ichiro Takeuchi

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Quantifying Statistical Significance of Neural Network Representation-Driven Hypotheses by Selective Inference.

Vo Nguyen Le Duy, Shogo Iwazaki, Ichiro Takeuchi

CoRR, 2020

Bayesian Experimental Design for Finding Reliable Level Set Under Input Uncertainty.

Shogo Iwazaki, Yu Inatsu, Ichiro Takeuchi

IEEE Access, 2020