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» Kernel Methods for Revealed Preference Analysis
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ECAI
2010
Springer
13 years 5 months ago
Kernel Methods for Revealed Preference Analysis
In classical revealed preference analysis we are given a sequence of linear prices (i.e., additive over goods) and an agent's demand at each of the prices. The problem is to d...
Sébastien Lahaie
ICB
2007
Springer
176views Biometrics» more  ICB 2007»
13 years 8 months ago
A Novel Null Space-Based Kernel Discriminant Analysis for Face Recognition
The symmetrical decomposition is a powerful method to extract features for image recognition. It reveals the significant discriminative information from the mirror image of symmetr...
Tuo Zhao, Zhizheng Liang, David Zhang, Yahui Liu
ICIP
2001
IEEE
14 years 6 months ago
Study of embedded font context and kernel space methods for improved videotext recognition
Videotext refers to text superimposed on video frames. A videotext based Multimedia Description Scheme has recently been adopted into the MPEG-7 standard. A study of published wor...
Chitra Dorai, Hrishikesh Aradhye, Jae-Chang Shim
ICPR
2008
IEEE
13 years 11 months ago
Object recognition using graph spectral invariants
Graph structures have been proved important in high level-vision since they can be used to represent structural and relational arrangements of objects in a scene. One of the probl...
Bai Xiao, Richard C. Wilson, Edwin R. Hancock
IJCNN
2006
IEEE
13 years 10 months ago
Information Theoretic Angle-Based Spectral Clustering: A Theoretical Analysis and an Algorithm
— Recent work has revealed a close connection between certain information theoretic divergence measures and properties of Mercer kernel feature spaces. Specifically, it has been...
Robert Jenssen, Deniz Erdogmus, Jose C. Principe