1088 search results - page 25 / 218 » A Bayesian Approach to Tackling Hard Computational Problems |
GECCO
2007
Springer
14 years 1 months ago
2007
Springer
Bayesian Networks are today used in various fields and domains due to their inherent ability to deal with uncertainty. Learning Bayesian Networks, however is an NP-Hard task [7]....
JUCS
2008
13 years 7 months ago
2008
: Evolutionary algorithms are effective search tools for tackling difficult optimization problems. In this paper an algorithm based on living processes where cooperation is the mai...
ICPR
2010
IEEE
13 years 11 months ago
2010
IEEE
The paper introduces a framework for clustering data objects in a similarity-based context. The aim is to cluster objects into a given number of classes without imposing a hard pa...
AI
2010
Springer
13 years 7 months ago
2010
Springer
Bayesian networks (BNs) are used to represent and ef ciently compute with multi-variate probability distributions in a wide range of disciplines. One of the main approaches to per...
TEC
2010
13 years 2 months ago
2010
Estimation of distribution algorithms (EDAs) are widely used in stochastic optimization. Impressive experimental results have been reported in the literature. However, little work ...