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» Regularized Linear Models in Stacked Generalization
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MCS
2009
Springer
10 years 2 months ago
Regularized Linear Models in Stacked Generalization
Abstract. Stacked generalization is a flexible method for multiple classifier combination; however, it tends to overfit unless the combiner function is sufficiently smooth. Prev...
Samuel Robert Reid, Gregory Z. Grudic
IPMI
2011
Springer
9 years 27 days ago
Generalized Sparse Regularization with Application to fMRI Brain Decoding
Many current medical image analysis problems involve learning thousands or even millions of model parameters from extremely few samples. Employing sparse models provides an effecti...
Bernard Ng, Rafeef Abugharbieh
NN
2002
Springer
224views Neural Networks» more  NN 2002»
9 years 9 months ago
Optimal design of regularization term and regularization parameter by subspace information criterion
The problem of designing the regularization term and regularization parameter for linear regression models is discussed. Previously, we derived an approximation to the generalizat...
Masashi Sugiyama, Hidemitsu Ogawa
FSTTCS
2004
Springer
10 years 2 months ago
Symbolic Reachability Analysis of Higher-Order Context-Free Processes
We consider the problem of symbolic reachability analysis of higher-order context-free processes. These models are generalizations of the context-free processes (also called BPA pr...
Ahmed Bouajjani, Antoine Meyer
TNN
1998
100views more  TNN 1998»
9 years 9 months ago
A dynamical system perspective of structural learning with forgetting
—Structural learning with forgetting is an established method of using Laplace regularization to generate skeletal artificial neural networks. In this paper we develop a continu...
D. A. Miller, J. M. Zurada
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