Randomized Gaussian Process Upper Confidence Bound with Tighter Bayesian Regret Bounds

Gaussian process upper confidence bound (GP-UCB) is a theoretically promising approach for black-box optimization; however, the confidence parameter \(\beta\) is considerably large in the theorem and chosen heuristically in practice. Then, randomized GP-UCB (RGP-UCB) uses a randomized confidence par...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	arXiv.org 2023-06
Hauptverfasser:	Takeno, Shion, Yu Inatsu, Karasuyama, Masayuki
Format:	Artikel
Sprache:	eng
Schlagworte:	Bayesian analysis Gaussian process Optimization Parameters Probability distribution functions
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!