Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Optimal Detection For Sparse Mixtures   Detection of sparse signals arises in a wide range of modern scientific
studies. The focus so far has been mainly on Gaussian mixture models. In this
paper, we consider the detection problem under a general sparse mixture model
and obtain an explicit expression for the detection boundary. It is shown that
the fundamental limits of detection is governed by the behavior of the
log-likelihood ratio evaluated at an appropriate quantile of the null
distribution. We also establish the adaptive optimality of the higher criticism
procedure across all sparse mixtures satisfying certain mild regularity
conditions. In particular, the general results obtained in this paper recover
and extend in a unified manner the previously known results on sparse detection
far beyond the conventional Gaussian model and other exponential families.

27
The categories of this paper are: comp-gas
24
The categories of this paper are: dg-ga
23
The categories of this paper are: solv-int
15
The categories of this paper are: nucl-ex
30
The categories of this paper are: q-alg
21
The categories of this paper are: adap-org
19
The categories of this paper are: eess
25
The categories of this paper are: patt-sol
9
The categories of this paper are: nlin
34
The categories of this paper are: chem-ph
0
The categories of this paper are: hep-ph
13
The categories of this paper are: quant-ph
37
The categories of this paper are: supr-con
26
The categories of this paper are: bayes-an
6
The categories of this paper are: astro-ph
35
The categories of this paper are: mtrl-th