Contrastive Unsupervised Learning of Semantic Representations: A Theoretical Framework – Off the convex path
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[paper](/doc/?uri=https%3A%2F%2Farxiv.org%2Fabs%2F1902.09229). Why do objectives similar the one used by word2vec succeed in such diverse settings? ("Contrastive Unsupervised Representation Learning" (CURL)) > In contrastive learning the objective used at test time is very different from the training objective: generalization error is not the right way to think about this. -> a framework that formalizes the notion of semantic similarity that is implicitly used by these algorithms > **if the unsupervised loss happens to be small at the end of contrastive learning then the resulting representations perform well on downstream classification**
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