Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Signal and Noise Statistics Oblivious Orthogonal Matching Pursuit   Orthogonal matching pursuit (OMP) is a widely used algorithm for recovering
sparse high dimensional vectors in linear regression models. The optimal
performance of OMP requires \textit{a priori} knowledge of either the sparsity
of regression vector or noise statistics. Both these statistics are rarely
known \textit{a priori} and are very difficult to estimate. In this paper, we
present a novel technique called residual ratio thresholding (RRT) to operate
OMP without any \textit{a priori} knowledge of sparsity and noise statistics
and establish finite sample and large sample support recovery guarantees for
the same. Both analytical results and numerical simulations in real and
synthetic data sets indicate that RRT has a performance comparable to OMP with
\textit{a priori} knowledge of sparsity and noise statistics.

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The categories of this paper are: q-alg
14
The categories of this paper are: math-ph
12
The categories of this paper are: nucl-th
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The categories of this paper are: supr-con
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The categories of this paper are: plasm-ph
5
The categories of this paper are: gr-qc
32
The categories of this paper are: atom-ph
4
The categories of this paper are: cond-mat
11
The categories of this paper are: hep-lat
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The categories of this paper are: chao-dyn
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The categories of this paper are: hep-th
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The categories of this paper are: q-fin
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The categories of this paper are: physics
23
The categories of this paper are: solv-int
34
The categories of this paper are: chem-ph
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The categories of this paper are: comp-gas