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Towards Scalable Bayesian Optimization via Gradient-Informed Bayesian Neural Networks
Georgios Makrygiorgos, Joshua Hang Sai Ip, Ali Mesbah
Bayesian optimization (BO) is a widely used method for data-driven optimization that generally relies on zeroth-order data of objective function to construct probabilistic surrogat…
cs.LG2025
User Preference Meets Pareto-Optimality in Multi-Objective Bayesian Optimization
Joshua Hang Sai Ip, Ankush Chakrabarty, Ali Mesbah +1
Incorporating user preferences into multi-objective Bayesian optimization (MOBO) allows for personalization of the optimization procedure. Preferences are often abstracted in the f…