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[HTML][HTML] Imprecise bayesian optimization
Bayesian optimization (BO) with Gaussian processes (GPs) surrogate models is widely used
to optimize analytically unknown and expensive-to-evaluate functions. In this paper, we …
to optimize analytically unknown and expensive-to-evaluate functions. In this paper, we …
Semi-supervised learning guided by the generalized Bayes rule under soft revision
We provide a theoretical and computational investigation of the Gamma-Maximin method
with soft revision, which was recently proposed as a robust criterion for pseudo-label …
with soft revision, which was recently proposed as a robust criterion for pseudo-label …
A Statistical Case Against Empirical Human-AI Alignment
J Rodemann, EG Arias, C Luther, C Jansen… - arxiv preprint arxiv …, 2025 - arxiv.org
Empirical human-AI alignment aims to make AI systems act in line with observed human
behavior. While noble in its goals, we argue that empirical alignment can inadvertently …
behavior. While noble in its goals, we argue that empirical alignment can inadvertently …