Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: On the Equivalence of Generative and Discriminative Formulations of the
  Sequential Dependence Model   The sequential dependence model (SDM) is a popular retrieval model which is
based on the theory of probabilistic graphical models. While it was originally
introduced by Metzler and Croft as a Markov Random Field (aka discriminative
probabilistic model), in this paper we demonstrate that it is equivalent to a
generative probabilistic model.
  To build an foundation for future retrieval models, this paper details the
axiomatic underpinning of the SDM model as discriminative and generative
probabilistic model. The only difference arises whether model parameters are
estimated in log-space or Multinomial-space. We demonstrate that
parameter-estimation with grid-tuning is negatively impacting the generative
formulation, an effect that vanishes when parameters are estimated with
coordinate-gradient descent. This is concerning, since empirical differences
may be falsely attributed to improved models.

5
The categories of this paper are: gr-qc
27
The categories of this paper are: comp-gas
4
The categories of this paper are: cond-mat
29
The categories of this paper are: funct-an
36
The categories of this paper are: cmp-lg
33
The categories of this paper are: plasm-ph
11
The categories of this paper are: hep-lat
26
The categories of this paper are: bayes-an
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The categories of this paper are: adap-org
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The categories of this paper are: ao-sci
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The categories of this paper are: nlin
32
The categories of this paper are: atom-ph
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The categories of this paper are: eess
16
The categories of this paper are: stat
37
The categories of this paper are: supr-con
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The categories of this paper are: q-fin