Tag: informative

Informative missingness and its implications in semi-supervised learning arXiv:2512.04392v1 Announce Type: new Abstract: Semi-supervised learning (SSL) constructs classifiers using both labelled and unlabelled data. It leverages information from labelled samples, whose acquisition is often costly or labour-intensive, together with unlabelled data to enhance prediction performance. This defines an incomplete-data problem, which statistically can be formulated…