A Self-Paced Regularization Framework for Partial-Label Learning.
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DOI: 10.1109/tcyb.2020.2990908
Abstract: Partial-label learning (PLL) aims to solve the problem where each training instance is associated with a set of candidate labels, one of which is the correct label. Most PLL algorithms try to disambiguate the candidate… read more here.
Keywords: label; paced regularization; framework; label learning ... See more keywords