Online Expectation Maximization based algorithms for inference in Hidden Markov Models
نویسندگان
چکیده
منابع مشابه
Online Expectation Maximization based algorithms for inference in hidden Markov models
The Expectation Maximization (EM) algorithm is a versatile tool for model parameter estimation in latent data models. When processing large data sets or data stream however, EM becomes intractable since it requires the whole data set to be available at each iteration of the algorithm. In this contribution, a new generic online EM algorithm for model parameter inference in general Hidden Markov ...
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This is a supplementary material to the paper [7]. It contains technical discussions and/or results adapted from published papers. In Sections 2 and 3, we provide results useful for the proofs of some theorems in [7] which are close to existing results in the literature. It also contains, in Section 4, additional plots for the numerical analyses in [7, Section 3]. To make this supplement paper ...
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ژورنال
عنوان ژورنال: Electronic Journal of Statistics
سال: 2013
ISSN: 1935-7524
DOI: 10.1214/13-ejs789