Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Regularized Greedy Column Subset Selection   The Column Subset Selection Problem provides a natural framework for
unsupervised feature selection. Despite being a hard combinatorial optimization
problem, there exist efficient algorithms that provide good approximations. The
drawback of the problem formulation is that it incorporates no form of
regularization, and is therefore very sensitive to noise when presented with
scarce data. In this paper we propose a regularized formulation of this
problem, and derive a correct greedy algorithm that is similar in efficiency to
existing greedy methods for the unregularized problem. We study its adequacy
for feature selection and propose suitable formulations. Additionally, we
derive a lower bound for the error of the proposed problems. Through various
numerical experiments on real and synthetic data, we demonstrate the
significantly increased robustness and stability of our method, as well as the
improved conditioning of its output, all while remaining efficient for
practical use.

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The categories of this paper are: hep-ph
21
The categories of this paper are: adap-org
13
The categories of this paper are: quant-ph
10
The categories of this paper are: q-bio
29
The categories of this paper are: funct-an
11
The categories of this paper are: hep-lat
33
The categories of this paper are: plasm-ph
30
The categories of this paper are: q-alg
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The categories of this paper are: hep-ex
25
The categories of this paper are: patt-sol
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The categories of this paper are: astro-ph
12
The categories of this paper are: nucl-th
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The categories of this paper are: nucl-ex
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The categories of this paper are: q-fin
36
The categories of this paper are: cmp-lg
23
The categories of this paper are: solv-int