On Learning Conditional Random Fields for Stereo - Exploring Model Structures and Approximate Inference.
Christopher J. PalJerod J. WeinmanLam C. TranDaniel ScharsteinPublished in: Int. J. Comput. Vis. (2012)
Keyphrases
- conditional random fields
- structured prediction
- approximate inference
- probabilistic model
- undirected graphical models
- graphical models
- parameter learning
- efficient inference
- learning algorithm
- random fields
- learning process
- fully connected
- prior knowledge
- parameter estimation
- supervised learning
- loopy belief propagation
- hidden variables
- hidden markov models
- variational methods
- information retrieval
- crf model
- probabilistic graphical models
- exact inference
- bayesian inference
- belief propagation
- efficient learning
- dynamic bayesian networks
- markov networks
- probability distribution
- probabilistic inference
- message passing
- least squares