Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Variable selection for (realistic) stochastic blockmodels   Stochastic blockmodels provide a convenient representation of relations
between communities of nodes in a network. However, they imply a notion of
stochastic equivalence that is often unrealistic for real networks, and they
comprise large number of parameters that can make them hardly interpretable. We
discuss two extensions of stochastic blockmodels, and a recently proposed
variable selection approach based on penalized inference, which allows to infer
a sparse reduced graph summarizing relations between communities. We compare
this approach with maximum likelihood estimation on two datasets on
face-to-face interactions in a French primary school and on bill cosponsorships
in the Italian Parliament.

30
The categories of this paper are: q-alg
17
The categories of this paper are: q-fin
25
The categories of this paper are: patt-sol
1
The categories of this paper are: cs
19
The categories of this paper are: eess
6
The categories of this paper are: astro-ph
31
The categories of this paper are: ao-sci
33
The categories of this paper are: plasm-ph
14
The categories of this paper are: math-ph
2
The categories of this paper are: math
22
The categories of this paper are: chao-dyn
18
The categories of this paper are: econ
12
The categories of this paper are: nucl-th
11
The categories of this paper are: hep-lat
20
The categories of this paper are: acc-phys
36
The categories of this paper are: cmp-lg