New research details GP-TS convergence rates and introduces GP-CTS

By PulseAugur Editorial · [1 sources] · 2026-10-15 04:00

A new research paper details advancements in Gaussian Process Thompson Sampling (GP-TS) for efficient global optimization. The study establishes convergence rates for GP-TS under noiseless conditions, particularly for Matérn kernels. Researchers also introduced Gaussian Process Capped Thompson Sampling (GP-CTS), a modification designed to eliminate logarithmic penalties and achieve optimal convergence rates. AI

IMPACT Introduces a novel method for optimizing expensive black-box functions, potentially improving efficiency in various AI applications.

RANK_REASON Research paper published on arXiv detailing algorithmic improvements. [lever_c_demoted from research: ic=1 ai=1.0]

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Newsworthiness bucket: Tool; Research paper published on arXiv detailing algorithmic improvements. [lever_c_demoted from research: ic=1 ai=1.0]
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arXiv cs.LG TIER_1 English(EN) · Haowei Wang, Yilin Zheng · 2026-10-15 04:00

Convergence Rates of Gaussian Process Thompson Sampling for Efficient Global Optimization

arXiv:2610.19925v1 Announce Type: cross Abstract: Efficient global optimization aims to identify a global optimum of an expensive black-box function within a limited evaluation budget $N$. We investigate the convergence rates of Gaussian process Thompson sampling (GP-TS) under no…