Dynamic conditional random fields: factorized probabilistic models for labeling and segmenting sequence data.
Charles SuttonKhashayar RohanimaneshAndrew McCallumPublished in: ICML (2004)
Keyphrases
- sequence data
- dynamic conditional random fields
- probabilistic model
- image segmentation
- conditional random fields
- sequence classification
- graphical models
- bayesian inference
- generative model
- biological sequences
- latent variables
- sequence analysis
- bayesian networks
- unsupervised learning
- expectation maximization
- dynamic bayesian networks
- profile hidden markov models
- active learning
- conditional probabilities
- belief propagation
- topic models
- nucleotide sequences
- hidden variables
- markov networks
- binding sites
- transfer learning
- segmentation method
- active contours
- feature selection