Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Towards a HPC-oriented parallel implementation of a learning algorithm
  for bioinformatics applications   Background: The huge quantity of data produced in Biomedical research needs
sophisticated algorithmic methodologies for its storage, analysis, and
processing. High Performance Computing (HPC) appears as a magic bullet in this
challenge. However, several hard to solve parallelization and load balancing
problems arise in this context. Here we discuss the HPC-oriented implementation
of a general purpose learning algorithm, originally conceived for DNA analysis
and recently extended to treat uncertainty on data (U BRAIN). The U-BRAIN
algorithm is a learning algorithm that finds a Boolean formula in disjunctive
normal form (DNF), of approximately minimum complexity, that is consistent with
a set of data (instances) which may have missing bits. The conjunctive terms of
the formula are computed in an iterative way by identifying, from the given
data, a family of sets of conditions that must be satisfied by all the positive
instances and violated by all the negative ones; such conditions allow the
computation of a set of coefficients (relevances) for each attribute (literal),
that form a probability distribution, allowing the selection of the term
literals. The great versatility that characterizes it, makes U-BRAIN applicable
in many of the fields in which there are data to be analyzed. However the
memory and the execution time required by the running are of O(n3) and of O(n5)
order, respectively, and so, the algorithm is unaffordable for huge data sets.

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The categories of this paper are: atom-ph
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The categories of this paper are: mtrl-th
27
The categories of this paper are: comp-gas
17
The categories of this paper are: q-fin
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The categories of this paper are: nucl-th
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The categories of this paper are: q-alg
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The categories of this paper are: bayes-an
0
The categories of this paper are: hep-ph
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The categories of this paper are: dg-ga
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The categories of this paper are: funct-an
2
The categories of this paper are: math
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The categories of this paper are: eess
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The categories of this paper are: econ
4
The categories of this paper are: cond-mat
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The categories of this paper are: nlin
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The categories of this paper are: acc-phys