2019
A Theoretical Analysis of Contrastive Unsupervised Representation Learning
ICML 2019oral
Recent empirical works have successfully used unlabeled data to learn feature representations that are broadly useful in downstream classification tasks. Several of these methods are reminiscent of the well-known word2vec embedding algorithm: leveraging availability of pairs of semantically “similar…