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2025 ICML ICML 2025

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

Abstract

No abstract available. No abstract was captured for this paper when its proceedings were scraped - most often an older edition published without one online. How the corpus is built.

🌉 Interdisciplinary Bridge - Artificial Intelligence and Mathematics & Optimization and Reinforcement Learning

Authors

Shogo Iwazaki, Shion Takeno

Topics

Machine Learning > Optimization & Theory > Bayesian Inference Reinforcement Learning > Methods > Policy Learning Mathematics & Optimization > Optimization > Continuous Optimization

Keywords

gaussian process regret noise variance phased elimination maximum posterior variance rkhs norm
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