LaRW: boosting open-set semi-supervised learning with label-guided re-weighting

The superior performance of traditional Semi-Supervised Learning (SSL) methods are generally achieved in strictly data-constrained scenarios, e.g. the class distribution of labeled and unlabeled data is matched. However, in realistic scenarios, unlabeled data is gathered from a variety of sources an...

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