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stat.ML2025
Wasserstein Barycenter Gaussian Process based Bayesian Optimization
Antonio Candelieri, Andrea Ponti, Francesco Archetti
Gaussian Process based Bayesian Optimization is a widely applied algorithm to learn and optimize under uncertainty, well-known for its sample efficiency. However, recently -- and m…
stat.ML2020
Composition of kernel and acquisition functions for High Dimensional Bayesian Optimization
Antonio Candelieri, Ilaria Giordani, Riccardo Perego +1
Bayesian Optimization has become the reference method for the global optimization of black box, expensive and possibly noisy functions. Bayesian Op-timization learns a probabilisti…