CoMatch: Semi-supervised Learning with Contrastive Graph Regularization

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Other Links: arxiv.org

Abstract:

Semi-supervised learning has been an effective paradigm for leveraging unlabeled data to reduce the reliance on labeled data. We propose CoMatch, a new semi-supervised learning method that unifies dominant approaches and addresses their limitations. CoMatch jointly learns two representations of the training data, their class probabiliti...More

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