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» Support Vector Machines for Multi-class Classification
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DAGM
2007
Springer
14 years 26 days ago
Greedy-Based Design of Sparse Two-Stage SVMs for Fast Classification
Cascades of classifiers constitute an important architecture for fast object detection. While boosting of simple (weak) classifiers provides an established framework, the design of...
Rezaul Karim, Martin Bergtholdt, Jörg H. Kapp...
TKDD
2008
113views more  TKDD 2008»
13 years 8 months ago
Privacy-preserving classification of vertically partitioned data via random kernels
We propose a novel privacy-preserving support vector machine (SVM) classifier for a data matrix A whose input feature columns are divided into groups belonging to different entiti...
Olvi L. Mangasarian, Edward W. Wild, Glenn Fung
ICASSP
2011
IEEE
13 years 20 days ago
An SVM based classification approach to speech separation
Monaural speech separation is a very challenging task. CASAbased systems utilize acoustic features to produce a time-frequency (T-F) mask. In this study, we propose a classificat...
Kun Han, DeLiang Wang
AVSS
2007
IEEE
14 years 3 months ago
Improved one-class SVM classifier for sounds classification
This paper proposes to apply optimized One-Class Support Vector Machines (1-SVMs) as a discriminative framework in order to address a specific audio classification problem. Firs...
Asma Rabaoui, Manuel Davy, Stéphane Rossign...
DMIN
2008
145views Data Mining» more  DMIN 2008»
13 years 10 months ago
Privacy-Preserving Classification of Horizontally Partitioned Data via Random Kernels
We propose a novel privacy-preserving nonlinear support vector machine (SVM) classifier for a data matrix A whose columns represent input space features and whose individual rows ...
Olvi L. Mangasarian, Edward W. Wild