Contrastive learning, multi-view redundancy, and linear models
ALT, pp. 1179-1206, 2021.
Self-supervised learning is an empirically successful approach to unsupervised learning based on creating artificial supervised learning problems. A popular self-supervised approach to representation learning is contrastive learning, which leverages naturally occurring pairs of similar and dissimilar data points, or multiple views of th...More
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