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cs.LG2026
Online Sharp-Calibrated Bayesian Optimization
Marshal Arijona Sinaga, Julien Martinelli, Teemu Turpeinen +1
Bayesian optimization (BO) is a widely used framework for optimizing expensive black-box functions, commonly based on Gaussian process (GP) surrogate models. Its effectiveness reli…
cs.LG2025
Robust and Computation-Aware Gaussian Processes
Marshal Arijona Sinaga, Julien Martinelli, Samuel Kaski
Gaussian processes (GPs) are widely used for regression and optimization tasks such as Bayesian optimization (BO) due to their expressiveness and principled uncertainty estimates.…
cs.LG2024
Anchor-Based Heteroscedastic Noise for Preferential Bayesian Optimization
Marshal Arijona Sinaga, Julien Martinelli, Samuel Kaski
Preferential Bayesian optimization (PBO) learns latent utilities from pairwise comparisons, but most existing methods assume homoscedastic comparison noise. This is inadequate in h…