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GECCO
2005
Springer
153views Optimization» more  GECCO 2005»
14 years 8 days ago
Evolving neural network ensembles for control problems
In neuroevolution, a genetic algorithm is used to evolve a neural network to perform a particular task. The standard approach is to evolve a population over a number of generation...
David Pardoe, Michael S. Ryoo, Risto Miikkulainen
ESWA
2008
124views more  ESWA 2008»
13 years 6 months ago
A hybrid financial analysis model for business failure prediction
Accounting frauds have continuously happened all over the world. This leads to the need of predicting business failures. Statistical methods and machine learning techniques have b...
Shi-Ming Huang, Chih-Fong Tsai, David C. Yen, Yin-...
NN
2006
Springer
13 years 6 months ago
Self-organizing neural networks to support the discovery of DNA-binding motifs
Identification of the short DNA sequence motifs that serve as binding targets for transcription factors is an important challenge in bioinformatics. Unsupervised techniques from t...
Shaun Mahony, Panayiotis V. Benos, Terry J. Smith,...
JSAC
2006
120views more  JSAC 2006»
13 years 6 months ago
A Tutorial on Cross-Layer Optimization in Wireless Networks
This tutorial paper overviews recent developments in optimization-based approaches for resource allocation problems in wireless systems. We begin by overviewing important results i...
Xiaojun Lin, Ness B. Shroff, R. Srikant
UAI
1996
13 years 8 months ago
Bayesian Learning of Loglinear Models for Neural Connectivity
This paper presents a Bayesian approach to learning the connectivity structure of a group of neurons from data on configuration frequencies. A major objective of the research is t...
Kathryn B. Laskey, Laura Martignon