Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Propagation via Kernelization: The Vertex Cover Constraint   The technique of kernelization consists in extracting, from an instance of a
problem, an essentially equivalent instance whose size is bounded in a
parameter k. Besides being the basis for efficient param-eterized algorithms,
this method also provides a wealth of information to reason about in the
context of constraint programming. We study the use of kernelization for
designing propagators through the example of the Vertex Cover constraint. Since
the classic kernelization rules often correspond to dominance rather than
consistency, we introduce the notion of "loss-less" kernel. While our
preliminary experimental results show the potential of the approach, they also
show some of its limits. In particular, this method is more effective for
vertex covers of large and sparse graphs, as they tend to have, relatively,
smaller kernels.

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The categories of this paper are: mtrl-th
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The categories of this paper are: gr-qc
0
The categories of this paper are: hep-ph
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The categories of this paper are: chao-dyn
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The categories of this paper are: physics
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The categories of this paper are: hep-ex
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The categories of this paper are: ao-sci
23
The categories of this paper are: solv-int
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The categories of this paper are: supr-con
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The categories of this paper are: econ
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The categories of this paper are: math
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The categories of this paper are: nlin
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The categories of this paper are: acc-phys
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The categories of this paper are: dg-ga
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The categories of this paper are: adap-org
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The categories of this paper are: astro-ph