Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Regular decomposition of large graphs and other structures: scalability
  and robustness towards missing data   A method for compression of large graphs and matrices to a block structure is
further developed. Szemer\'edi's regularity lemma is used as a generic
motivation of the significance of stochastic block models. Another ingredient
of the method is Rissanen's minimum description length principle (MDL). We
continue our previous work on the subject, considering cases of missing data
and scaling of algorithms to extremely large size of graphs. In this way it
would be possible to find out a large scale structure of a huge graphs of
certain type using only a tiny part of graph information and obtaining a
compact representation of such graphs useful in computations and visualization.

14
The categories of this paper are: math-ph
36
The categories of this paper are: cmp-lg
9
The categories of this paper are: nlin
15
The categories of this paper are: nucl-ex
12
The categories of this paper are: nucl-th
20
The categories of this paper are: acc-phys
27
The categories of this paper are: comp-gas
6
The categories of this paper are: astro-ph
22
The categories of this paper are: chao-dyn
4
The categories of this paper are: cond-mat
31
The categories of this paper are: ao-sci
30
The categories of this paper are: q-alg
7
The categories of this paper are: hep-th
34
The categories of this paper are: chem-ph
16
The categories of this paper are: stat
13
The categories of this paper are: quant-ph