31 search results - page 3 / 7 » Topology Free Hidden Markov Models: Application to Backgroun... |
ECML
2006
Springer
13 years 11 months ago
2006
Springer
The standard approach for learning Markov Models with Hidden State uses the Expectation-Maximization framework. While this approach had a significant impact on several practical ap...
BMCBI
2005
13 years 7 months ago
2005
Background: G- Protein coupled receptors (GPCRs) comprise the largest group of eukaryotic cell surface receptors with great pharmacological interest. A broad range of native ligan...
BMCBI
2010
13 years 7 months ago
2010
Background: Traditional algorithms for hidden Markov model decoding seek to maximize either the probability of a state path or the number of positions of a sequence assigned to th...
BMCBI
2005
13 years 7 months ago
2005
Background: Baum-Welch training is an expectation-maximisation algorithm for training the emission and transition probabilities of hidden Markov models in a fully automated way. I...
JCSS
2007
13 years 7 months ago
2007
Hidden Markov models (HMMs) are often used for biological sequence annotation. Each sequence feature is represented by a collection of states with the same label. In annotating a ...