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» On Kernel Methods for Relational Learning
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FLAIRS
2008
14 years 16 days ago
Evolutionary Learning of Dynamic Naive Bayesian Classifiers
Naive Bayesian classifiers work well in data sets with independent attributes. However, they perform poorly when the attributes are dependent or when there are one or more irrelev...
Miguel A. Palacios-Alonso, Carlos A. Brizuela, Lui...
TEC
2002
133views more  TEC 2002»
13 years 9 months ago
Learning and optimization using the clonal selection principle
The clonal selection principle is used to explain the basic features of an adaptive immune response to an antigenic stimulus. It establishes the idea that only those cells that rec...
Leandro Nunes de Castro, Fernando J. Von Zuben
CVPR
2011
IEEE
13 years 6 months ago
Learning the Easy Things First: Self-Paced Visual Category Discovery
Objects vary in their visual complexity, yet existing discovery methods perform “batch” clustering, paying equal attention to all instances simultaneously—regardless of the ...
Yong Jae Lee, Kristen Grauman
TNN
2010
234views Management» more  TNN 2010»
13 years 4 months ago
Novel maximum-margin training algorithms for supervised neural networks
This paper proposes three novel training methods, two of them based on the back-propagation approach and a third one based on information theory for Multilayer Perceptron (MLP) bin...
Oswaldo Ludwig, Urbano Nunes
SP
2002
IEEE
128views Security Privacy» more  SP 2002»
13 years 9 months ago
Fitting hidden Markov models to psychological data
Markov models have been used extensively in psychology of learning. Applications of hidden Markov models are rare however. This is partially due to the fact that comprehensive stat...
Ingmar Visser, Maartje E. J. Raijmakers, Peter C. ...