Title :
New trends in Markov models and related learning to restore data
Author :
Forbes, Florence ; Pieczynski, Wojciech
Author_Institution :
Lab. Jean Kuntzman, INRIA Grenoble Rhone-Alpes, Grenoble, France
Abstract :
We present recent approaches that extend standard Markov models and increase their modelling power. These capabilities are illustrated in the cited published works and more recently in the contributions to the Special Session on Markov models of the IEEE International Workshop on Machine Learning for Signal Processing, 2009. However, the review is not exhaustive and major older works may be missing.
Keywords :
Markov processes; data handling; learning (artificial intelligence); Markov models; data restoration; machine learning; signal processing; Approximation algorithms; Bayesian methods; Computational modeling; Conferences; Hidden Markov models; Image restoration; Iterative algorithms; Machine learning; Signal processing; Stochastic processes;
Conference_Titel :
Machine Learning for Signal Processing, 2009. MLSP 2009. IEEE International Workshop on
Conference_Location :
Grenoble
Print_ISBN :
978-1-4244-4947-7
Electronic_ISBN :
978-1-4244-4948-4
DOI :
10.1109/MLSP.2009.5306255
