Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A model selection approach for multiple sequence segmentation and
  dimensionality reduction   In this paper we consider the problem of segmenting $n$ aligned random
sequences of equal length $m$, into a finite number of independent blocks. We
propose to use a penalized maximum likelihood criterion to infer simultaneously
the number of points of independence as well as the position of each one of
these points. We show how to compute the estimator efficiently by means of a
dynamic programming algorithm with time complexity $O(m^2n)$. We also propose
another algorithm, called hierarchical algorithm, that provides an
approximation to the estimator when the sample size increases and runs in time
$O(mn)$. Our main theoretical result is the proof of almost sure consistency of
the estimator and the convergence of the hierarchical algorithm when the sample
size $n$ grows to infinity. We illustrate the convergence of these algorithms
through some simulation examples and we apply the method to a real protein
sequence alignment of Ebola Virus.

23
The categories of this paper are: solv-int
29
The categories of this paper are: funct-an
36
The categories of this paper are: cmp-lg
2
The categories of this paper are: math
1
The categories of this paper are: cs
17
The categories of this paper are: q-fin
18
The categories of this paper are: econ
3
The categories of this paper are: physics
31
The categories of this paper are: ao-sci
11
The categories of this paper are: hep-lat
34
The categories of this paper are: chem-ph
32
The categories of this paper are: atom-ph
15
The categories of this paper are: nucl-ex
37
The categories of this paper are: supr-con
19
The categories of this paper are: eess
27
The categories of this paper are: comp-gas