Fast Sparse Gaussian Process Methods: The Informative Vector Machine

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at Dept of Signal Theory and Communications, Universidad Carlos III de Madrid, Spain on Jul 3, 2007 [pdf]
Neil D. Lawrence, University of Sheffield

Abstract

Gaussian processes are a non parametric approach to learning regression models. In this talk we will given a brief review of the use of Gaussian processes for regression. We will then introduce the informative vector machine approach to learning Gaussian processes for Classification on large scale data sets. We will show extensions of the method including multi-task learning, semi-supervised learning and learning invariances.

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