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204
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ICANN
2001
Springer
15 years 11 months ago
Fast Training of Support Vector Machines by Extracting Boundary Data
Support vector machines have gotten wide acceptance for their high generalization ability for real world applications. But the major drawback is slow training for classification p...
Shigeo Abe, Takuya Inoue
ICANN
2001
Springer
15 years 11 months ago
Feature Extraction Using ICA
In manipulating data such as in supervised learning, we often extract new features from original features for the purpose of reducing the dimensions of feature space and achieving ...
Nojun Kwak, Chong-Ho Choi, Jin-Young Choi
189
Voted
ICANN
2001
Springer
15 years 11 months ago
Incremental Support Vector Machine Learning: A Local Approach
Abstract. In this paper, we propose and study a new on-line algorithm for learning a SVM based on Radial Basis Function Kernel: Local Incremental Learning of SVM or LISVM. Our meth...
Liva Ralaivola, Florence d'Alché-Buc
151
Voted
ICANN
2001
Springer
15 years 11 months ago
Sparse Kernel Regressors
Sparse kernel regressors have become popular by applying the support vector method to regression problems. Although this approach has been shown to exhibit excellent generalization...
Volker Roth
ICANN
2001
Springer
15 years 11 months ago
Clustering of EEG-Segments Using Hierarchical Agglomerative Methods and Self-Organizing Maps
EEG segments recorded during microsleep events were transformed to the frequency domain and were subsequently clustered without the common summation of power densities in spectral ...
David Sommer, Martin Golz