4 papers
An Empirical Study on Ensemble-Based Transfer Learning Bayesian Optimisation with Mixed Variable Types
Natasha Trinkle, Huong Ha, Jeffrey Chan
Bayesian optimisation is a sample efficient method for finding a global optimum of expensive black-box objective functions. Historic datasets from related problems can be exploited…
MOBO-OSD: Batch Multi-Objective Bayesian Optimization via Orthogonal Search Directions
Lam Ngo, Huong Ha, Jeffrey Chan +1
Bayesian Optimization (BO) is a powerful tool for optimizing expensive black-box objective functions. While extensive research has been conducted on the single-objective optimizati…
MOCA-HESP: Meta High-dimensional Bayesian Optimization for Combinatorial and Mixed Spaces via Hyper-ellipsoid Partitioning
Lam Ngo, Huong Ha, Jeffrey Chan +1
High-dimensional Bayesian Optimization (BO) has attracted significant attention in recent research. However, existing methods have mainly focused on optimizing in continuous domain…
BOIDS: High-dimensional Bayesian Optimization via Incumbent-guided Direction Lines and Subspace Embeddings
Lam Ngo, Huong Ha, Jeffrey Chan +1
When it comes to expensive black-box optimization problems, Bayesian Optimization (BO) is a well-known and powerful solution. Many real-world applications involve a large number of…