Wasserstein Auto-Encoders: Difference between revisions
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= Introduction = | = Introduction = | ||
Unsupervised representation learning from large unlabeled datasets has been an area of active research. For example, in the context of computer vision, one can leverage the practically unlimited amount of unlabeled images and videos to learn good intermediate representations, which can then be used on a variety of supervised learning tasks such as image classification. | |||
= Motivation = | = Motivation = | ||
Revision as of 22:18, 11 March 2018
Introduction
Unsupervised representation learning from large unlabeled datasets has been an area of active research. For example, in the context of computer vision, one can leverage the practically unlimited amount of unlabeled images and videos to learn good intermediate representations, which can then be used on a variety of supervised learning tasks such as image classification.