PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

A pragmatic Bayesian approach to predictive uncertainty
Iain Murray and Ed Snelson
In: Machine Learning Challenges. Evaluating Predictive Uncertainty, Visual Object Classification, and Recognising Tectual Entailment.: First PASCAL Machine Learning Challenges Workshop, MLCW 2005, Southampton, UK, April 11-13, 2005, Revised Selected Papers Lecture Notes in Computer Science , 3944 / 2006 . (2006) Springer , pp. 33-40. ISBN 3 540 33427 0

Abstract

We describe an approach to regression based on building a probabilistic model with the aid of visualization. The "stereopsis" data set in the predictive uncertainty challenge is used as a case study, for which we constructed a mixture of neural network experts model. We describe both the ideal Bayesian approach and computational shortcuts required to obtain timely results.

EPrint Type:Book Section
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Computational, Information-Theoretic Learning with Statistics
Learning/Statistics & Optimisation
Theory & Algorithms
ID Code:1166
Deposited By:Iain Murray
Deposited On:19 November 2005