Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Learning Bayesian Networks from Incomplete Data with Stochastic Search
  Algorithms   This paper describes stochastic search approaches, including a new stochastic
algorithm and an adaptive mutation operator, for learning Bayesian networks
from incomplete data. This problem is characterized by a huge solution space
with a highly multimodal landscape. State-of-the-art approaches all involve
using deterministic approaches such as the expectation-maximization algorithm.
These approaches are guaranteed to find local maxima, but do not explore the
landscape for other modes. Our approach evolves structure and the missing data.
We compare our stochastic algorithms and show they all produce accurate
results.

15
The categories of this paper are: nucl-ex
20
The categories of this paper are: acc-phys
8
The categories of this paper are: hep-ex
10
The categories of this paper are: q-bio
17
The categories of this paper are: q-fin
28
The categories of this paper are: alg-geom
29
The categories of this paper are: funct-an
35
The categories of this paper are: mtrl-th
26
The categories of this paper are: bayes-an
37
The categories of this paper are: supr-con
22
The categories of this paper are: chao-dyn
18
The categories of this paper are: econ
24
The categories of this paper are: dg-ga
6
The categories of this paper are: astro-ph
30
The categories of this paper are: q-alg
12
The categories of this paper are: nucl-th