77 citations · 584 across the 84 of their papers we have counts for
4 papers · 1 filter
Private Outsourced Bayesian Optimization
Dmitrii Kharkovskii, Zhongxiang Dai, Bryan Kian Hsiang Low
This paper presents the private-outsourced-Gaussian process-upper confidence bound (PO-GP-UCB) algorithm, which is the first algorithm for privacy-preserving Bayesian optimization…
Federated Bayesian Optimization via Thompson Sampling
Zhongxiang Dai, Kian Hsiang Low, Patrick Jaillet
Bayesian optimization (BO) is a prominent approach to optimizing expensive-to-evaluate black-box functions. The massive computational capability of edge devices such as mobile phon…
R2-B2: Recursive Reasoning-Based Bayesian Optimization for No-Regret Learning in Games
Zhongxiang Dai, Yizhou Chen, Kian Hsiang Low +2
This paper presents a recursive reasoning formalism of Bayesian optimization (BO) to model the reasoning process in the interactions between boundedly rational, self-interested age…
Nonmyopic Gaussian Process Optimization with Macro-Actions
Dmitrii Kharkovskii, Chun Kai Ling, Kian Hsiang Low
This paper presents a multi-staged approach to nonmyopic adaptive Gaussian process optimization (GPO) for Bayesian optimization (BO) of unknown, highly complex objective functions…