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Abstract -A Bayesian approach for classification of Markov sources whose parameters are not explicitly known is developed and studied.
Abstract: A Bayesian approach for classification of Markov sources whose parameters are not explicitly known is developed and studied.
ISSN Information: Print ISSN: 0018-9448 Electronic ISSN: 1557-9654
DOI: 10.1109/18.86998
DOI: 10.1109/18.86998
The proposed classifier is based on sequential estimation of the parameters of the sources, and it is closely related to earlier proposed universal tests ...
Bibliographic details on A Bayesian approach for classification of Markov sources.
The proposed classifier is based upon sequential estimation of the parameters of the sources and it is closely related to earlier proposed universal tests under ...
Jul 30, 2022 · Abstract: In the reinforcement learning literature, there are many algorithms developed for either Contextual Bandit (CB) or Markov Decision ...
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distributions. Keywords: Markov chains; Bayesian inference; large deviations; moderate deviations. AMS 2000 Subject Classification: Primary 60F10.
Sep 28, 2015 · It is then described how, through a summary of some key algorithms, many of the potential difficulties associated with a Bayesian approach can ...
Request PDF | A Bayesian approach based on a Markov-chain Monte Carlo method for damage detection under unknown sources of variability | In the Structural ...
Markov models, Classification, Time series, Bayes' rule. ... We present a method for recursive computation of pe(yl, ... chains (see, e.g., [27]). LEMMA 4.