Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Error Estimation in Approximate Bayesian Belief Network Inference   We can perform inference in Bayesian belief networks by enumerating
instantiations with high probability thus approximating the marginals. In this
paper, we present a method for determining the fraction of instantiations that
has to be considered such that the absolute error in the marginals does not
exceed a predefined value. The method is based on extreme value theory.
Essentially, the proposed method uses the reversed generalized Pareto
distribution to model probabilities of instantiations below a given threshold.
Based on this distribution, an estimate of the maximal absolute error if
instantiations with probability smaller than u are disregarded can be made.

29
The categories of this paper are: funct-an
18
The categories of this paper are: econ
10
The categories of this paper are: q-bio
22
The categories of this paper are: chao-dyn
31
The categories of this paper are: ao-sci
3
The categories of this paper are: physics
11
The categories of this paper are: hep-lat
12
The categories of this paper are: nucl-th
34
The categories of this paper are: chem-ph
28
The categories of this paper are: alg-geom
5
The categories of this paper are: gr-qc
15
The categories of this paper are: nucl-ex
26
The categories of this paper are: bayes-an
33
The categories of this paper are: plasm-ph
6
The categories of this paper are: astro-ph
30
The categories of this paper are: q-alg