4 papers
Scalable Batch Bayesian Optimization Via Subspace Acquisition Functions
Dawei Zhan, Zhaoxi Zeng, Shuoxiao Wei +1
Extending Bayesian optimization to batch evaluation can enable the designer to make the most use of parallel computing technology. However, most of current batch approaches do not…
Variable-preconditioned transformed primal-dual method for generalized Wasserstein Gradient Flows
Jin Zeng, Dawei Zhan, Ruchi Guo +1
We propose a Variable-Preconditioned Transformed Primal-Dual (VPTPD) method for solving generalized Wasserstein gradient flows based on the structure-preserving JKO scheme. This is…
An Adaptive Dropout Approach for High-Dimensional Bayesian Optimization
Jundi Huang, Dawei Zhan
Bayesian optimization (BO) is a widely used algorithm for solving expensive black-box optimization problems. However, its performance decreases significantly on high-dimensional pr…
Expected Coordinate Improvement for High-Dimensional Bayesian Optimization
Dawei Zhan
Bayesian optimization (BO) algorithm is very popular for solving low-dimensional expensive optimization problems. Extending Bayesian optimization to high dimension is a meaningful…