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ICANN
2001
Springer
2001
Springer
Learning and Prediction of the Nonlinear Dynamics of Biological Neurons with Support Vector Machines
15 years 2 months ago
Based on biological data we examine the ability of Support Vector Machines (SVMs) with gaussian kernels to learn and predict the nonlinear dynamics of single biological neurons. We...
109
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JMLR
2002
14 years 9 months ago
2002
A central problem in learning is selection of an appropriate model. This is typically done by estimating the unknown generalization errors of a set of models to be selected from a...
ICDM
2005
IEEE
15 years 3 months ago
2005
IEEE
Binary classification is a core data mining task. For large datasets or real-time applications, desirable classifiers are accurate, fast, and need no parameter tuning. We presen...
104
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ICML
2003
IEEE
15 years 10 months ago
2003
IEEE
This paper presents a novel discriminative learning technique for label sequences based on a combination of the two most successful learning algorithms, Support Vector Machines an...
118
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ESANN
2006
14 years 11 months ago
2006
Random Forests were introduced by Breiman for feature (variable) selection and improved predictions for decision tree models. The resulting model is often superior to AdaBoost and ...