4 papers
Approximation of Box Decomposition Algorithm for Fast Hypervolume-Based Multi-Objective Optimization
Shuhei Watanabe
Hypervolume (HV)-based Bayesian optimization (BO) is one of the standard approaches for multi-objective decision-making. However, the computational cost of optimizing the acquisiti…
Tree-Structured Parzen Estimator Can Solve Black-Box Combinatorial Optimization More Efficiently
Kenshin Abe, Yunzhuo Wang, Shuhei Watanabe
Tree-structured Parzen estimator (TPE) is a versatile hyperparameter optimization (HPO) method supported by popular HPO tools. Since these HPO tools have been developed in line wit…
Derivation of Output Correlation Inferences for Multi-Output (aka Multi-Task) Gaussian Process
Shuhei Watanabe
Gaussian process (GP) is arguably one of the most widely used machine learning algorithms in practice. One of its prominent applications is Bayesian optimization (BO). Although the…
Derivation of Closed Form of Expected Improvement for Gaussian Process Trained on Log-Transformed Objective
Shuhei Watanabe
Expected Improvement (EI) is arguably the most widely used acquisition function in Bayesian optimization. However, it is often challenging to enhance the performance with EI due to…