84 search results - page 6 / 17 » Utilizing Variational Optimization to Learn Markov Random Fi... |
CVPR
2007
IEEE
15 years 11 months ago
2007
IEEE
Markov Random Field (MRF) models are a popular tool for vision and image processing. Gaussian MRF models are particularly convenient to work with because they can be implemented u...
ICML
2007
IEEE
15 years 10 months ago
2007
IEEE
Conditional random fields (CRFs) are graphical models for modeling the probability of labels given the observations. They have traditionally been trained with using a set of obser...
JMLR
2010
14 years 4 months ago
2010
Continuous-time Bayesian networks is a natural structured representation language for multicomponent stochastic processes that evolve continuously over time. Despite the compact r...
ICML
2004
IEEE
15 years 10 months ago
2004
IEEE
Conditional Random Fields (CRFs; Lafferty, McCallum, & Pereira, 2001) provide a flexible and powerful model for learning to assign labels to elements of sequences in such appl...
CORR
2011
Springer
14 years 4 months ago
2011
Springer
We describe a new variational lower-bound on the minimum energy configuration of a planar binary Markov Random Field (MRF). Our method is based on adding auxiliary nodes to every...