Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Online Learning in Discrete Hidden Markov Models   We present and analyse three online algorithms for learning in discrete
Hidden Markov Models (HMMs) and compare them with the Baldi-Chauvin Algorithm.
Using the Kullback-Leibler divergence as a measure of generalisation error we
draw learning curves in simplified situations. The performance for learning
drifting concepts of one of the presented algorithms is analysed and compared
with the Baldi-Chauvin algorithm in the same situations. A brief discussion
about learning and symmetry breaking based on our results is also presented.

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The categories of this paper are: hep-th
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The categories of this paper are: cond-mat
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The categories of this paper are: gr-qc
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The categories of this paper are: nlin
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The categories of this paper are: adap-org
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The categories of this paper are: comp-gas
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The categories of this paper are: hep-ex
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The categories of this paper are: q-fin
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The categories of this paper are: funct-an
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The categories of this paper are: cmp-lg
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The categories of this paper are: cs
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The categories of this paper are: math-ph
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The categories of this paper are: hep-lat
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The categories of this paper are: q-bio
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The categories of this paper are: plasm-ph
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The categories of this paper are: patt-sol