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Learning imprecise hidden Markov models

Arthur Van Camp UGent (2011) BENE@WORK, Presentations.
abstract
We present a method for learning imprecise local uncertainty models in stationary hidden Markov models. If there is enough data to justify precise local uncertainty models, then existing learning algorithms, such as the Baum–Welch algorithm, can be used. When there is not enough evidence to justify precise models, the method we suggest here has a number of interesting features.
Please use this url to cite or link to this publication:
author
organization
year
type
conference
publication status
published
subject
in
BENE@WORK, Presentations
conference name
BENE@WORK : 1st workshop for PhD students from Belgium and The Netherlands working on Probabilistic Graphical Models
conference location
Brussels, Belgium
conference start
2011-12-07
conference end
2011-12-07
language
English
UGent publication?
no
classification
C3
copyright statement
I have retained and own the full copyright for this publication
id
2019788
handle
http://hdl.handle.net/1854/LU-2019788
alternative location
http://bnatwork.etro.vub.ac.be/bnatwork/WORKSHOP.ashx
date created
2012-02-05 18:39:36
date last changed
2016-12-19 15:36:52
@inproceedings{2019788,
  abstract     = {We present a method for learning imprecise local uncertainty models in stationary hidden Markov models. If there is enough data to justify precise local uncertainty models, then existing learning algorithms, such as the Baum--Welch algorithm, can be used. When there is not enough evidence to justify precise models, the method we suggest here has a number of interesting features.},
  author       = {Van Camp, Arthur},
  booktitle    = {BENE@WORK, Presentations},
  language     = {eng},
  location     = {Brussels, Belgium},
  title        = {Learning imprecise hidden Markov models},
  url          = {http://bnatwork.etro.vub.ac.be/bnatwork/WORKSHOP.ashx},
  year         = {2011},
}

Chicago
Van Camp, Arthur. 2011. “Learning Imprecise Hidden Markov Models.” In BENE@WORK, Presentations.
APA
Van Camp, Arthur. (2011). Learning imprecise hidden Markov models. BENE@WORK, Presentations. Presented at the BENE@WORK : 1st workshop for PhD students from Belgium and The Netherlands working on Probabilistic Graphical Models.
Vancouver
1.
Van Camp A. Learning imprecise hidden Markov models. BENE@WORK, Presentations. 2011.
MLA
Van Camp, Arthur. “Learning Imprecise Hidden Markov Models.” BENE@WORK, Presentations. 2011. Print.