PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Embedding Sample Points Uncertainty Measures in Learning Algorithms
Dario Malchiodi
Nonlinear Analysis 2006.

Abstract

Learning algorithms consider a sample consisting of pairs (pattern, label) and output a decision rule, possibly: (i) associating each pattern with the corresponding label, and (ii) generalizing to new patterns drawn from the same distribution of the original sample. This work proposes a set of methodologies to be applied to existing learning strategies in order to deal with more complex kinds of data sets, carrying also a quantitative measure on the quality of each label.

EPrint Type:Article
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
Theory & Algorithms
ID Code:3525
Deposited By:Dario Malchiodi
Deposited On:11 February 2008