Convergence Rates of Gaussian Process Thompson Sampling for Efficient Global Optimization
stat.ML, cs.LG
Submitted: 2026-10-14
Updated: 2026-10-14
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Sources
- A Tutorial on Bayesian Optimization
- Improved Regret Analysis in Gaussian Process Bandits: Optimality for Noiseless Reward, RKHS norm, and Non-Stationary Variance
- Frequentist Regret Analysis of Gaussian Process Thompson Sampling via Fractional Posteriors
- Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design
- Improved Regret Analysis for Parallel Gaussian Process Bandit Optimization
- Simple-regret rates and minimax optimality of fixed-prior expected improvement in Mat\'ern and squared-exponential RKHSs
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