most citedRevisiting Deep Semi-supervised Learning: An Empirical Distribution Alignment Framework and Its Generalization Bound

2 citations · 2 across the 1 of their papers we have counts for

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1 paper

cs.CV2022★ 2 cited

Revisiting Deep Semi-supervised Learning: An Empirical Distribution Alignment Framework and Its Generalization Bound

Feiyu Wang, Qin Wang, Wen Li +2

In this work, we revisit the semi-supervised learning (SSL) problem from a new perspective of explicitly reducing empirical distribution mismatch between labeled and unlabeled samp…