Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Expectation-maximization for logistic regression   We present a family of expectation-maximization (EM) algorithms for binary
and negative-binomial logistic regression, drawing a sharp connection with the
variational-Bayes algorithm of Jaakkola and Jordan (2000). Indeed, our results
allow a version of this variational-Bayes approach to be re-interpreted as a
true EM algorithm. We study several interesting features of the algorithm, and
of this previously unrecognized connection with variational Bayes. We also
generalize the approach to sparsity-promoting priors, and to an online method
whose convergence properties are easily established. This latter method
compares favorably with stochastic-gradient descent in situations with marked
collinearity.

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The categories of this paper are: atom-ph
12
The categories of this paper are: nucl-th
0
The categories of this paper are: hep-ph
18
The categories of this paper are: econ
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The categories of this paper are: adap-org
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The categories of this paper are: cmp-lg
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The categories of this paper are: chao-dyn
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The categories of this paper are: eess
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The categories of this paper are: funct-an
7
The categories of this paper are: hep-th
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The categories of this paper are: comp-gas
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The categories of this paper are: nlin
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The categories of this paper are: cs
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The categories of this paper are: plasm-ph
31
The categories of this paper are: ao-sci
10
The categories of this paper are: q-bio