Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Inference and learning in probabilistic logic programs using weighted
  Boolean formulas   Probabilistic logic programs are logic programs in which some of the facts
are annotated with probabilities. This paper investigates how classical
inference and learning tasks known from the graphical model community can be
tackled for probabilistic logic programs. Several such tasks such as computing
the marginals given evidence and learning from (partial) interpretations have
not really been addressed for probabilistic logic programs before.
  The first contribution of this paper is a suite of efficient algorithms for
various inference tasks. It is based on a conversion of the program and the
queries and evidence to a weighted Boolean formula. This allows us to reduce
the inference tasks to well-studied tasks such as weighted model counting,
which can be solved using state-of-the-art methods known from the graphical
model and knowledge compilation literature. The second contribution is an
algorithm for parameter estimation in the learning from interpretations
setting. The algorithm employs Expectation Maximization, and is built on top of
the developed inference algorithms.
  The proposed approach is experimentally evaluated. The results show that the
inference algorithms improve upon the state-of-the-art in probabilistic logic
programming and that it is indeed possible to learn the parameters of a
probabilistic logic program from interpretations.

2
The categories of this paper are: math
24
The categories of this paper are: dg-ga
29
The categories of this paper are: funct-an
11
The categories of this paper are: hep-lat
16
The categories of this paper are: stat
4
The categories of this paper are: cond-mat
25
The categories of this paper are: patt-sol
0
The categories of this paper are: hep-ph
18
The categories of this paper are: econ
28
The categories of this paper are: alg-geom
35
The categories of this paper are: mtrl-th
33
The categories of this paper are: plasm-ph
9
The categories of this paper are: nlin
13
The categories of this paper are: quant-ph
10
The categories of this paper are: q-bio
32
The categories of this paper are: atom-ph