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» Optimal feature selection for support vector machines
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TASLP
2008
108views more  TASLP 2008»
13 years 9 months ago
A Regression Approach to Music Emotion Recognition
Content-based retrieval has emerged in the face of content explosion as a promising approach to information access. In this paper, we focus on the challenging issue of recognizing ...
Yi-Hsuan Yang, Yu-Ching Lin, Ya-Fan Su, Homer H. C...
SG
2010
Springer
14 years 1 months ago
Sketch-Based Interfaces: Exploiting Spatio-temporal Context for Automatic Stroke Grouping
In this paper, we investigate how discourse context in the form of short-term memory can be exploited to automatically group consecutive strokes in digital freehand sketching. With...
Lutz Dickmann, Tobias Lensing, Robert Porzel, Rain...
ISCI
2007
130views more  ISCI 2007»
13 years 9 months ago
Learning to classify e-mail
In this paper we study supervised and semi-supervised classification of e-mails. We consider two tasks: filing e-mails into folders and spam e-mail filtering. Firstly, in a sup...
Irena Koprinska, Josiah Poon, James Clark, Jason C...
ICCV
2001
IEEE
14 years 11 months ago
The Variable Bandwidth Mean Shift and Data-Driven Scale Selection
We present two solutions for the scale selection problem in computer vision. The rst one is completely nonparametric and is based on the the adaptive estimation of the normalized ...
Dorin Comaniciu, Visvanathan Ramesh, Peter Meer
ICANN
2005
Springer
14 years 2 months ago
The LCCP for Optimizing Kernel Parameters for SVM
Abstract. Tuning hyper-parameters is a necessary step to improve learning algorithm performances. For Support Vector Machine classifiers, adjusting kernel parameters increases dra...
Sabri Boughorbel, Jean-Philippe Tarel, Nozha Bouje...