2 papers
stat.ML2020
Finding Optimal Points for Expensive Functions Using Adaptive RBF-Based Surrogate Model Via Uncertainty Quantification
Ray-Bing Chen, Yuan Wang, C. F. Jeff Wu
Global optimization of expensive functions has important applications in physical and computer experiments. It is a challenging problem to develop efficient optimization scheme, be…
stat.ML2018
Greedy Active Learning Algorithm for Logistic Regression Models
Hsiang-Ling Hsu, Yuan-Chin Ivan Chang, Ray-Bing Chen
We study a logistic model-based active learning procedure for binary classification problems, in which we adopt a batch subject selection strategy with a modified sequential experi…