Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Bayesian methods for low-rank matrix estimation: short survey and
  theoretical study   The problem of low-rank matrix estimation recently received a lot of
attention due to challenging applications. A lot of work has been done on
rank-penalized methods and convex relaxation, both on the theoretical and
applied sides. However, only a few papers considered Bayesian estimation. In
this paper, we review the different type of priors considered on matrices to
favour low-rank. We also prove that the obtained Bayesian estimators, under
suitable assumptions, enjoys the same optimality properties as the ones based
on penalization.

36
The categories of this paper are: cmp-lg
17
The categories of this paper are: q-fin
4
The categories of this paper are: cond-mat
15
The categories of this paper are: nucl-ex
24
The categories of this paper are: dg-ga
34
The categories of this paper are: chem-ph
11
The categories of this paper are: hep-lat
26
The categories of this paper are: bayes-an
13
The categories of this paper are: quant-ph
10
The categories of this paper are: q-bio
23
The categories of this paper are: solv-int
21
The categories of this paper are: adap-org
35
The categories of this paper are: mtrl-th
7
The categories of this paper are: hep-th
5
The categories of this paper are: gr-qc
6
The categories of this paper are: astro-ph