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» Generalized Discriminant Analysis Using a Kernel Approach
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TIT
2008
224views more  TIT 2008»
15 years 1 months ago
Graph-Based Semi-Supervised Learning and Spectral Kernel Design
We consider a framework for semi-supervised learning using spectral decomposition-based unsupervised kernel design. We relate this approach to previously proposed semi-supervised l...
Rie Johnson, Tong Zhang
143
Voted
CVPR
2007
IEEE
16 years 3 months ago
Kernel Sharing With Joint Boosting For Multi-Class Concept Detection
Object/scene detection by discriminative kernel-based classification has gained great interest due to its promising performance and flexibility. In this paper, unlike traditional ...
Wei Jiang, Shih-Fu Chang, Alexander C. Loui
125
Voted
ICCV
2007
IEEE
16 years 3 months ago
Structure from Statistics - Unsupervised Activity Analysis using Suffix Trees
Models of activity structure for unconstrained environments are generally not available a priori. Recent representational approaches to this end are limited by their computational...
Raffay Hamid, Siddhartha Maddi, Aaron F. Bobick, I...
110
Voted
ESANN
2007
15 years 3 months ago
A novel kernel-based method for local pattern extraction in random process signals
In many applications, one is interested to detect certain patterns in random process signals. We consider a class of random process signals which contain sub similarities at rando...
Majid Beigi, Andreas Zell
95
Voted
MICCAI
2008
Springer
16 years 3 months ago
Regularized Discriminative Direction for Shape Difference Analysis
Abstract. The "discriminative direction" has been proven useful to reveal the subtle difference between two anatomical shape classes. When a shape moves along this direct...
Luping Zhou, Richard I. Hartley, Lei Wang, Paulett...