Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A neural network and iterative optimization hybrid for Dempster-Shafer
  clustering   In this paper we extend an earlier result within Dempster-Shafer theory
["Fast Dempster-Shafer Clustering Using a Neural Network Structure," in Proc.
Seventh Int. Conf. Information Processing and Management of Uncertainty in
Knowledge-Based Systems (IPMU 98)] where a large number of pieces of evidence
are clustered into subsets by a neural network structure. The clustering is
done by minimizing a metaconflict function. Previously we developed a method
based on iterative optimization. While the neural method had a much lower
computation time than iterative optimization its average clustering performance
was not as good. Here, we develop a hybrid of the two methods. We let the
neural structure do the initial clustering in order to achieve a high
computational performance. Its solution is fed as the initial state to the
iterative optimization in order to improve the clustering performance.

14
The categories of this paper are: math-ph
23
The categories of this paper are: solv-int
34
The categories of this paper are: chem-ph
7
The categories of this paper are: hep-th
27
The categories of this paper are: comp-gas
19
The categories of this paper are: eess
15
The categories of this paper are: nucl-ex
0
The categories of this paper are: hep-ph
5
The categories of this paper are: gr-qc
2
The categories of this paper are: math
12
The categories of this paper are: nucl-th
37
The categories of this paper are: supr-con
17
The categories of this paper are: q-fin
35
The categories of this paper are: mtrl-th
6
The categories of this paper are: astro-ph
21
The categories of this paper are: adap-org