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Assessment of various initialization strategies for the Expectation-Maximization algorithm for Hidden Semi-Markov Models with multiple categorical sequences
Abstract : In this study, we propose a method called sequence breaking framework to search high local maximum of the likelihood by providing starting values based on the observations for the Expectation-Maximization algorithm, for Hidden semi-Markov model parameter estimation. The method is shown to be efficient on several datasets with multiple categorical sequences.
Cited literature [12 references]
https://hal.inria.fr/hal-02129122
Contributor : Brice Olivier <>
Submitted on : Tuesday, May 14, 2019 - 3:55:21 PM
Last modification on : Thursday, November 19, 2020 - 1:04:02 PM
Contributor : Brice Olivier <>
Submitted on : Tuesday, May 14, 2019 - 3:55:21 PM
Last modification on : Thursday, November 19, 2020 - 1:04:02 PM
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olivier2019assessment.pdf
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