DoubleMatch: Improving Semi-Supervised Learning with Self-Supervision. (arXiv:2205.05575v1 [cs.LG])

Web: http://arxiv.org/abs/2205.05575

Following the success of supervised learning, semi-supervised learning (SSL)
is now becoming increasingly popular. SSL is a family of methods, which in
addition to a labeled training set, also use a sizable collection of unlabeled
data for fitting a model. Most of the recent successful SSL methods are based
on pseudo-labeling approaches: letting confident model predictions act as
training labels. While these methods have shown impressive results on many
benchmark datasets, a drawback of this approach is that not all …

arxiv learning semi-supervised semi-supervised learning supervised learning