Web: http://arxiv.org/abs/2107.08943

June 17, 2022, 1:11 a.m. | Jongjin Park, Sukmin Yun, Jongheon Jeong, Jinwoo Shin

cs.LG updates on arXiv.org arxiv.org

Semi-supervised learning (SSL) is one of the most promising paradigms to
circumvent the expensive labeling cost for building a high-performance model.
Most existing SSL methods conventionally assume both labeled and unlabeled data
are drawn from the same (class) distribution. However, unlabeled data may
include out-of-class samples in practice; those that cannot have one-hot
encoded labels from a closed-set of classes in label data, i.e. unlabeled data
is an open-set. In this paper, we introduce OpenCoS, a method for handling this …

arxiv cv data learning open semi-supervised semi-supervised learning set supervised learning

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