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» Interval discriminant analysis using support vector machines
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TNN
2010
143views Management» more  TNN 2010»
14 years 6 months ago
Using unsupervised analysis to constrain generalization bounds for support vector classifiers
Abstract--A crucial issue in designing learning machines is to select the correct model parameters. When the number of available samples is small, theoretical sample-based generali...
Sergio Decherchi, Sandro Ridella, Rodolfo Zunino, ...
ICDM
2007
IEEE
109views Data Mining» more  ICDM 2007»
15 years 6 months ago
A Support Vector Approach to Censored Targets
Censored targets, such as the time to events in survival analysis, can generally be represented by intervals on the real line. In this paper, we propose a novel support vector tec...
Pannagadatta K. Shivaswamy, Wei Chu, Martin Jansch...
ICIAR
2005
Springer
15 years 5 months ago
On the Individuality of the Iris Biometric
We consider quantitatively establishing the discriminative power of iris biometric data. It is difficult, however, to establish that any biometric modality is capable of distingui...
Sungsoo Yoon, Seung-Seok Choi, Sung-Hyuk Cha, Yill...
IJCAI
2007
15 years 1 months ago
Detection of Cognitive States from fMRI Data Using Machine Learning Techniques
Over the past decade functional Magnetic Resonance Imaging (fMRI) has emerged as a powerful technique to locate activity of human brain while engaged in a particular task or cogni...
Vishwajeet Singh, Krishna P. Miyapuram, Raju S. Ba...
IJCNN
2000
IEEE
15 years 4 months ago
A Neural Support Vector Network Architecture with Adaptive Kernels
In the Support Vector Machines (SVM) framework, the positive-definite kernel can be seen as representing a fixed similarity measure between two patterns, and a discriminant func...
Pascal Vincent, Yoshua Bengio