Author

Arto Klami

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Jul 2026

Maximally Robust Satisficing Bayesian Optimization

Many design tasks can be cast as black-box function optimization, enabling use of Bayesian optimization to find an ideal design with minimal number of trials. However, often we do not actually need the optimum but instead a sufficiently good solution is enough, for instance a material that is durable enough for its int...

Samuli Kinnunen, P. Mikkola, Antti Niskanen et al. · arXiv.org · 0 citations

#machine learning Mar 2026

Simplex-to-Euclidean Bijection for Conjugate and Calibrated Multiclass Gaussian Process

This approach uses Aitchison geometry to map simplex-valued class probabilities to an unconstrained Euclidean representation, turning classification into a GP regression problem with fewer latent dimensions than standard multi-class GP classifiers.

Bernardo Williams, Harsha Vardhan Tetali, Arto Klami et al. · arXiv.org · 0 citations