Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: An MAP Estimation for Between-Class Variance   Probabilistic linear discriminant analysis (PLDA) has been widely used in
open-set verification tasks, such as speaker verification. A potential issue of
this model is that the training set often contains limited number of classes,
which makes the estimation for the between-class variance unreliable. This
unreliable estimation often leads to degraded generalization. In this paper, we
present an MAP estimation for the between-class variance, by employing an
Inverse-Wishart prior. A key problem is that with hierarchical models such as
PLDA, the prior is placed on the variance of class means while the likelihood
is based on class members, which makes the posterior inference intractable. We
derive a simple MAP estimation for such a model, and test it in both PLDA
scoring and length normalization. In both cases, the MAP-based estimation
delivers interesting performance improvement.

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The categories of this paper are: stat
22
The categories of this paper are: chao-dyn
6
The categories of this paper are: astro-ph
10
The categories of this paper are: q-bio
30
The categories of this paper are: q-alg
18
The categories of this paper are: econ
17
The categories of this paper are: q-fin
34
The categories of this paper are: chem-ph
35
The categories of this paper are: mtrl-th
4
The categories of this paper are: cond-mat
28
The categories of this paper are: alg-geom
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The categories of this paper are: atom-ph
29
The categories of this paper are: funct-an
11
The categories of this paper are: hep-lat
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The categories of this paper are: math-ph
12
The categories of this paper are: nucl-th