PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Polynomial Conditional Random Fields for signal processing
T-M-T Do and T Artières
In: ECAI 2006, 28 Aug - 01 sept 2006, Italy.

Abstract

We describe polynomial Conditional Random Fields for signal processing tasks. It is a hybrid model that combines the ability of Polynomial Hidden Markov models for modeling complex dynamic signals and the discriminant power of Conditional Random Fields. We investigate the learning of these models and report experimental results on on-line handwriting recognition task.

PDF - Requires Adobe Acrobat Reader or other PDF viewer.
EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
ID Code:2833
Deposited By:Thierry Artieres
Deposited On:22 November 2006