3 papers
cs.LG2026
Bayesian Optimization with Structured Measurements: A Vector-Valued RKHS Framework
Wenbin Wang, Colin N. Jones
Bayesian optimization (BO) is an efficient framework for optimizing expensive black-box functions. However, it is typically formulated as learning an end-to-end mapping from inputs…
cs.LG2026
PolyFormer: learning efficient reformulations for scalable optimization under complex physical constraints
Yilin Wen, Yi Guo, Bo Zhao +4
Real-world optimization problems are often constrained by complex physical laws that limit computational scalability. These constraints are inherently tied to complex regions, and…
cs.LG2024
Principled Bayesian Optimisation in Collaboration with Human Experts
Wenjie Xu, Masaki Adachi, Colin N. Jones +1
Bayesian optimisation for real-world problems is often performed interactively with human experts, and integrating their domain knowledge is key to accelerate the optimisation proc…