New Online EM algorithms for general Hidden Markov Models. Application to the SLAM problem

Abstract :

In this contribution, new online EM algorithms are proposed to perform inference in general hidden Markov models. These algorithms update the parameter at some deterministic times and use Sequential Monte Carlo methods to compute approximations of ltering distribu- tions. In this paper, the performance of these algorithms are highlighted in the chal- lenging framework of Simultaneous Localization and Mapping.

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Conference papers
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https://hal.telecom-paristech.fr/hal-02286254
Contributor : Telecomparis Hal <>
Submitted on : Friday, September 13, 2019 - 3:32:38 PM
Last modification on : Thursday, October 17, 2019 - 12:37:02 PM

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Sylvain Le Corff, Gersende Fort, Eric Moulines. New Online EM algorithms for general Hidden Markov Models. Application to the SLAM problem. LVA-ICA, Mar 2012, Tel-Aviv, Israel. ⟨hal-02286254⟩

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