4 papers
Improving Bayesian Optimization via Training-Aware Conditional Diffusion Models
Yilin Zheng, Haowei Wang, Szu Hui Ng +1
Bayesian optimization (BO) is a widely used approach for black-box optimization that uses a Gaussian process (GP) as a surrogate and guides sequential evaluations via an acquisitio…
An Online Non-Stationary Simulation Optimization Approach Based on Regime Switching
Jianglin Xia, Haowei Wang, Songhao Wang +1
Dynamic and evolving operational and economic environments present significant challenges for decision-making. We explore a simulation optimization problem characterized by non-sta…
Weighted Euclidean Distance Matrices over Mixed Continuous and Categorical Inputs for Gaussian Process Models
Mingyu Pu, Songhao Wang, Haowei Wang +1
Gaussian Process (GP) models are widely utilized as surrogate models in scientific and engineering fields. However, standard GP models are limited to continuous variables due to th…
Adjusted Expected Improvement for Cumulative Regret Minimization in Noisy Bayesian Optimization
Shouri Hu, Haowei Wang, Zhongxiang Dai +2
The expected improvement (EI) is one of the most popular acquisition functions for Bayesian optimization (BO) and has demonstrated good empirical performances in many applications…