Bayesian Active Learning for Censored Regression

arXiv:2402.11973v1 Announce Type: new
Abstract: Bayesian active learning is based on information theoretical approaches that focus on maximising the information that new observations provide to the model parameters. This is commonly done by maximising the Bayesian Active Learning by Disagreement (BALD) acquisitions function. However, we highlight that it is challenging to estimate BALD when the new data points are subject to censorship, where only clipped values of the targets are observed. To address this, we derive the entropy and the …

abstract acquisitions active learning arxiv bayesian cs.lg focus function highlight information parameters regression stat.ml the information type