Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Sequential Analysis in High Dimensional Multiple Testing and Sparse
  Recovery   This paper studies the problem of high-dimensional multiple testing and
sparse recovery from the perspective of sequential analysis. In this setting,
the probability of error is a function of the dimension of the problem. A
simple sequential testing procedure is proposed. We derive necessary conditions
for reliable recovery in the non-sequential setting and contrast them with
sufficient conditions for reliable recovery using the proposed sequential
testing procedure. Applications of the main results to several commonly
encountered models show that sequential testing can be exponentially more
sensitive to the difference between the null and alternative distributions (in
terms of the dependence on dimension), implying that subtle cases can be much
more reliably determined using sequential methods.

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The categories of this paper are: eess
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The categories of this paper are: bayes-an
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The categories of this paper are: q-alg
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The categories of this paper are: hep-lat
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The categories of this paper are: astro-ph
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The categories of this paper are: quant-ph
0
The categories of this paper are: hep-ph
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The categories of this paper are: supr-con
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The categories of this paper are: econ
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The categories of this paper are: math-ph
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The categories of this paper are: ao-sci
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The categories of this paper are: solv-int
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The categories of this paper are: dg-ga
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The categories of this paper are: patt-sol
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The categories of this paper are: alg-geom
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The categories of this paper are: comp-gas