Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Covariance Estimation in Elliptical Models with Convex Structure   We address structured covariance estimation in Elliptical distribution. We
assume it is a priori known that the covariance belongs to a given convex set,
e.g., the set of Toeplitz or banded matrices. We consider the General Method of
Moments (GMM) optimization subject to these convex constraints. Unfortunately,
GMM is still non-convex due to objective. Instead, we propose COCA - a convex
relaxation which can be efficiently solved. We prove that the relaxation is
tight in the unconstrained case for a finite number of samples, and in the
constrained case asymptotically. We then illustrate the advantages of COCA in
synthetic simulations with structured Compound Gaussian distributions. In these
examples, COCA outperforms competing methods as Tyler's estimate and its
projection onto a convex set.

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The categories of this paper are: q-alg
7
The categories of this paper are: hep-th
35
The categories of this paper are: mtrl-th
37
The categories of this paper are: supr-con
5
The categories of this paper are: gr-qc
12
The categories of this paper are: nucl-th
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The categories of this paper are: eess
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The categories of this paper are: atom-ph
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The categories of this paper are: comp-gas
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The categories of this paper are: nucl-ex
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The categories of this paper are: alg-geom
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The categories of this paper are: astro-ph
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The categories of this paper are: hep-ph
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The categories of this paper are: q-bio
33
The categories of this paper are: plasm-ph
20
The categories of this paper are: acc-phys