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EMMCVPR
2001
Springer
13 years 9 months ago
Designing the Minimal Structure of Hidden Markov Model by Bisimulation
Hidden Markov Models (HMMs) are an useful and widely utilized approach to the modeling of data sequences. One of the problems related to this technique is finding the optimal stru...
Manuele Bicego, Agostino Dovier, Vittorio Murino
DOCENG
2007
ACM
13 years 8 months ago
Structure and content analysis for html medical articles: a hidden markov model approach
We describe ongoing research on segmenting and labeling HTML medical journal articles. In contrast to existing approaches in which HTML tags usually serve as strong indicators, we...
Jie Zou, Daniel X. Le, George R. Thoma
DATAMINE
2006
83views more  DATAMINE 2006»
13 years 4 months ago
Structural Hidden Markov Models Using a Relation of Equivalence: Application to Automotive Designs
Standard hidden Markov models (HMM's) have been studied extensively in the last two decades. It is well known that these models assume state conditional independence of the ob...
Djamel Bouchaffra, Jun Tan
AAAI
1997
13 years 6 months ago
Model Minimization in Markov Decision Processes
Many stochastic planning problems can be represented using Markov Decision Processes (MDPs). A difficulty with using these MDP representations is that the common algorithms for so...
Thomas Dean, Robert Givan
CEC
2005
IEEE
13 years 10 months ago
Evolving hidden Markov models for protein secondary structure prediction
New results are presented for the prediction of secondary structure information for protein sequences using Hidden Markov Models (HMMs) evolved using a Genetic Algorithm (GA). We a...
Kyoung-Jae Won, Thomas Hamelryck, Adam Prügel...