PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

A Framework for Probability Density Estimation
John Shawe-Taylor and Alexander N. Dolia
In: AISTATS (AI and Statistics), March 21 - 24 2007, Puerto Rico.

Abstract

The paper introduces a new framework for learning probability density functions. A theoretical analysis suggests that we can tailor a distribution for a class of tasks by training it to fit a small subsample. Experimental evidence is given to support the theoretical analysis.

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EPrint Type:Conference or Workshop Item (Other)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
Theory & Algorithms
ID Code:2770
Deposited By:John Shawe-Taylor
Deposited On:22 November 2006

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