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Learning and generalization with the information bottleneck

Theoretical Computer Science, no. 29-30 (2010): 2696-2711

Cited by: 127|Views85
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Abstract

The Information Bottleneck is an information theoretic framework that finds concise representations for an 'input' random variable that are as relevant as possible for an 'output' random variable. This framework has been used successfully in various supervised and unsupervised applications. However, its learning theoretic properties and j...More

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