Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Sparse Representation Classification Beyond L1 Minimization and the
  Subspace Assumption   The sparse representation classifier (SRC) has been utilized in various
classification problems, which makes use of L1 minimization and works well for
image recognition satisfying a subspace assumption. In this paper we propose a
new implementation of SRC via screening, establish its equivalence to the
original SRC under regularity conditions, and prove its classification
consistency under a latent subspace model and contamination. The results are
demonstrated via simulations and real data experiments, where the new algorithm
achieves comparable numerical performance and significantly faster.

14
The categories of this paper are: math-ph
36
The categories of this paper are: cmp-lg
19
The categories of this paper are: eess
26
The categories of this paper are: bayes-an
33
The categories of this paper are: plasm-ph
28
The categories of this paper are: alg-geom
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The categories of this paper are: acc-phys
5
The categories of this paper are: gr-qc
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The categories of this paper are: chem-ph
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The categories of this paper are: dg-ga
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The categories of this paper are: comp-gas
2
The categories of this paper are: math
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The categories of this paper are: nlin
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The categories of this paper are: q-bio
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The categories of this paper are: nucl-th
4
The categories of this paper are: cond-mat