Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Weighted Linear Discriminant Analysis based on Class Saliency
  Information   In this paper, we propose a new variant of Linear Discriminant Analysis to
overcome underlying drawbacks of traditional LDA and other LDA variants
targeting problems involving imbalanced classes. Traditional LDA sets
assumptions related to Gaussian class distribution and neglects influence of
outlier classes, that might hurt in performance. We exploit intuitions coming
from a probabilistic interpretation of visual saliency estimation in order to
define saliency of a class in multi-class setting. Such information is then
used to redefine the between-class and within-class scatters in a more robust
manner. Compared to traditional LDA and other weight-based LDA variants, the
proposed method has shown certain improvements on facial image classification
problems in publicly available datasets.

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The categories of this paper are: comp-gas
22
The categories of this paper are: chao-dyn
8
The categories of this paper are: hep-ex
30
The categories of this paper are: q-alg
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The categories of this paper are: bayes-an
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The categories of this paper are: adap-org
7
The categories of this paper are: hep-th
5
The categories of this paper are: gr-qc
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The categories of this paper are: ao-sci
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The categories of this paper are: econ
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The categories of this paper are: plasm-ph
2
The categories of this paper are: math
35
The categories of this paper are: mtrl-th
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The categories of this paper are: patt-sol
34
The categories of this paper are: chem-ph
10
The categories of this paper are: q-bio