3 papers
cs.LG2026
Maximizing Reliability with Bayesian Optimization
Jack M. Buckingham, Ivo Couckuyt, Juergen Branke
Bayesian optimization (BO) is a popular, sample-efficient technique for expensive, black-box optimization. One such problem arising in manufacturing is that of maximizing the relia…
stat.ML2025
Knowledge Gradient for Multi-Objective Bayesian Optimization with Decoupled Evaluations
Jack M. Buckingham, Sebastian Rojas Gonzalez, Juergen Branke
Multi-objective Bayesian optimization aims to find the Pareto front of trade-offs between a set of expensive objectives while collecting as few samples as possible. In some cases,…
stat.ML2025
Bayesian Optimization for Non-Convex Two-Stage Stochastic Optimization Problems
Jack M. Buckingham, Ivo Couckuyt, Juergen Branke
Bayesian optimization is a sample-efficient method for solving expensive, black-box optimization problems. Stochastic programming concerns optimization under uncertainty where, typ…