Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Mutual Information in Community Detection with Covariate Information and
  Correlated Networks   We study the problem of community detection when there is covariate
information about the node labels and one observes multiple correlated
networks. We provide an asymptotic upper bound on the per-node mutual
information as well as a heuristic analysis of a multivariate performance
measure called the MMSE matrix. These results show that the combined effects of
seemingly very different types of information can be characterized explicitly
in terms of formulas involving low-dimensional estimation problems in additive
Gaussian noise. Our analysis is supported by numerical simulations.

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The categories of this paper are: chao-dyn
9
The categories of this paper are: nlin
4
The categories of this paper are: cond-mat
18
The categories of this paper are: econ
36
The categories of this paper are: cmp-lg
24
The categories of this paper are: dg-ga
8
The categories of this paper are: hep-ex
23
The categories of this paper are: solv-int
19
The categories of this paper are: eess
3
The categories of this paper are: physics
26
The categories of this paper are: bayes-an
7
The categories of this paper are: hep-th
0
The categories of this paper are: hep-ph
25
The categories of this paper are: patt-sol
29
The categories of this paper are: funct-an
13
The categories of this paper are: quant-ph