276 search results - page 30 / 56 » PAC-Learning of Markov Models with Hidden State |
ICML
2000
IEEE
14 years 9 months ago
2000
IEEE
Hidden Markov models (HMMs) are a powerful probabilistic tool for modeling sequential data, and have been applied with success to many text-related tasks, such as part-of-speech t...
BMCBI
2005
13 years 8 months ago
2005
Background: Probabilistic models for sequence comparison (such as hidden Markov models and pair hidden Markov models for proteins and mRNAs, or their context-free grammar counterp...
ICMLA
2004
13 years 9 months ago
2004
Predictive state representation (PSR) models for controlled dynamical systems have recently been proposed as an alternative to traditional models such as partially observable Mark...
CVPR
1998
IEEE
14 years 10 months ago
1998
IEEE
In previous work [14], we modify the hidden Markov model (HMM) framework to incorporate a global parametric variation in the output probabilities of the states of the HMM. Develop...
CORR
1999
Springer
13 years 8 months ago
1999
Springer
We present a technique which complements Hidden Markov Models by incorporating some lexicalized states representing syntactically uncommon words. 'Our approach examines the d...