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An Introduction to PAC-Bayesian Analysis

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Author/s

John Shawe-Taylor

About the resource/s

This resource corresponds to 9th video from the AI Excellence Lecture Series.

PAC-Bayesian Analysis is a framework in machine learning and statistics that combines ideas from the Probably Approximately Correct (PAC) learning framework and Bayesian probability theory. It is used to analyse the generalisation performance of machine learning algorithms.

Documents
Document File - An-Introduction-to-PAC-Bayesian

An-Introduction-to-PAC-Bayesian
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