Safe Semi-Supervised Contrastive Learning Using In-Distribution Data as Positive Examples

Min Gu Kwak, Hyungu Kahng, Seoung Bum Kim

Semi-supervised learning methods have shown promising results in solving many practical problems when only a few labels are available. The existing methods assume that the class di…