RDA: Reciprocal Distribution Alignment for Robust Semi-supervised Learning. (arXiv:2208.04619v2 [cs.LG] UPDATED)

In this work, we propose Reciprocal Distribution Alignment (RDA) to address
semi-supervised learning (SSL), which is a hyperparameter-free framework that
is independent of confidence threshold and works with both the matched
(conventionally) and the mismatched class distributions. Distribution mismatch
is an often overlooked but more general SSL scenario where the labeled and the
unlabeled data do not fall into the identical class distribution. This may lead
to the model not exploiting the labeled data reliably and drastically degrade
the performance …

alignment arxiv distribution learning lg semi-supervised semi-supervised learning supervised learning