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An Introduction to Statistical Learning Theory

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If you have a question about this talk, please contact Zoubin Ghahramani.

Machine Learning Tutorial Lecture

The tutorial will introduce the framework within which statistical learning theory studies the phenomenon of learning from data. The concept of the Vapnik-Chervonenkis dimension and its relation to probably approximately correct (PAC) learning will be introduced with sketches of some of the proof techniques. The failure of the classical PAC learning to analyse learning in high dimensional feature spaces will lead to the introduction of more advanced techniques that motivate the support vector machine optimisation. A summary of the limitations and potential applications of the techniques will lead into the discussion.

This talk is part of the Machine Learning @ CUED series.

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