Not All Unlabeled Data are Equal: Learning to Weight Data in Semi-supervised Learning Zhongzheng Ren

But not all unlabeled data are equal. In this paper we study how to use a different weight for every unlabeled example. Manual tuning of all those weights - as done in prior work - is no longer possible.