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» Boosted Optimization for Network Classification
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ECAI
2004
Springer
15 years 3 months ago
Towards Efficient Learning of Neural Network Ensembles from Arbitrarily Large Datasets
Advances in data collection technologies allow accumulation of large and high dimensional datasets and provide opportunities for learning high quality classification and regression...
Kang Peng, Zoran Obradovic, Slobodan Vucetic
IJCAI
2003
14 years 11 months ago
When Discriminative Learning of Bayesian Network Parameters Is Easy
Bayesian network models are widely used for discriminative prediction tasks such as classification. Usually their parameters are determined using 'unsupervised' methods ...
Hannes Wettig, Peter Grünwald, Teemu Roos, Pe...
ICML
2005
IEEE
15 years 10 months ago
Discriminative versus generative parameter and structure learning of Bayesian network classifiers
In this paper, we compare both discriminative and generative parameter learning on both discriminatively and generatively structured Bayesian network classifiers. We use either ma...
Franz Pernkopf, Jeff A. Bilmes
FLAIRS
2006
14 years 11 months ago
GFAM: Evolving Fuzzy ARTMAP Neural Networks
Fuzzy ARTMAP (FAM) is one of the best neural network architectures in solving classification problems. One of the limitations of Fuzzy ARTMAP that has been extensively reported in...
Ahmad Al-Daraiseh, Michael Georgiopoulos, Annie S....
ICARIS
2007
Springer
15 years 3 months ago
An Artificial Immune System-Inspired Multiobjective Evolutionary Algorithm with Application to the Detection of Distributed Comp
Today’s signature-based intrusion detection systems are reactive in nature and storage-limited. Their operation depends upon catching an instance of an intrusion or virus and en...
Charles R. Haag, Gary B. Lamont, Paul D. Williams,...