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BMCBI
2006
146views more  BMCBI 2006»
15 years 20 days ago
Optimized Particle Swarm Optimization (OPSO) and its application to artificial neural network training
Background: Particle Swarm Optimization (PSO) is an established method for parameter optimization. It represents a population-based adaptive optimization technique that is influen...
Michael Meissner, Michael Schmuker, Gisbert Schnei...
93
Voted
ICIP
2003
IEEE
16 years 2 months ago
A Bayesian approach to inclusion and performance analysis of using extra information in bioelectric inverse problems
Due to attenuation and spatial smoothing that occurs in the conducting media, the bioelectric inverse problem of estimating sources from remote measurements is ill-posed and solut...
Yesim Serinagaoglu, Dana H. Brooks, Robert S. MacL...
108
Voted
ICML
2010
IEEE
15 years 1 months ago
Modeling Interaction via the Principle of Maximum Causal Entropy
The principle of maximum entropy provides a powerful framework for statistical models of joint, conditional, and marginal distributions. However, there are many important distribu...
Brian Ziebart, J. Andrew Bagnell, Anind K. Dey
IPPS
2006
IEEE
15 years 6 months ago
Parallelization of module network structure learning and performance tuning on SMP
As an extension of Bayesian network, module network is an appropriate model for inferring causal network of a mass of variables from insufficient evidences. However learning such ...
Hongshan Jiang, Chunrong Lai, Wenguang Chen, Yuron...
PE
2006
Springer
114views Optimization» more  PE 2006»
15 years 16 days ago
On the performance of Internet worm scanning strategies
In recent years, fast spreading worms, such as Code Red, Slammer, Blaster and Sasser, have become one of the major threats to the security of the Internet. In order to defend agai...
Cliff Changchun Zou, Donald F. Towsley, Weibo Gong