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Learning in Markov models using the imprecise Dirichlet model

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The objective of our research is first of all the development of a method for learning the transition probabilities in (possibly hidden) Markov models using imprecise probabilities, and next the application of this method to some real-life problems. The learning model used will be the imprecise Dirichlet model, an extension of the precise Dirichlet model to the theory of imprecise probabilities. Possible applications are gene-sequence alignment and pre-fetching of web pages.

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Chicago
Quaeghebeur, Erik. 2002. “Learning in Markov Models Using the Imprecise Dirichlet Model.” In Interuniversity Attraction Pole IAP V/22 Study Day, Posters.
APA
Quaeghebeur, E. (2002). Learning in Markov models using the imprecise Dirichlet model. Interuniversity Attraction Pole IAP V/22 Study Day, Posters. Presented at the Interuniversity Attraction Pole IAP V/22 Study Day.
Vancouver
1.
Quaeghebeur E. Learning in Markov models using the imprecise Dirichlet model. Interuniversity Attraction Pole IAP V/22 Study Day, Posters. 2002.
MLA
Quaeghebeur, Erik. “Learning in Markov Models Using the Imprecise Dirichlet Model.” Interuniversity Attraction Pole IAP V/22 Study Day, Posters. 2002. Print.
@inproceedings{1974568,
  abstract     = {The objective of our research is first of all the development of a method for learning the transition probabilities in (possibly hidden) Markov models using imprecise probabilities, and next the application of this method to some real-life problems. The learning model used will be the imprecise Dirichlet model, an extension of the precise Dirichlet model to the theory of imprecise probabilities. Possible applications are gene-sequence alignment and pre-fetching of web pages.},
  author       = {Quaeghebeur, Erik},
  booktitle    = {Interuniversity Attraction Pole IAP V/22 Study Day, Posters},
  language     = {eng},
  location     = {Louvain-la-Neuve, Belgium},
  title        = {Learning in Markov models using the imprecise Dirichlet model},
  year         = {2002},
}