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» Generalized Discriminant Analysis Using a Kernel Approach
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OSDI
1996
ACM
13 years 10 months ago
Dealing with Disaster: Surviving Misbehaved Kernel Extensions
Today's extensible operating systems allow applications to modify kernel behavior by providing mechanisms for application code to run in the kernel address space. The advanta...
Margo I. Seltzer, Yasuhiro Endo, Christopher Small...
CVPR
2006
IEEE
14 years 11 months ago
Graph Laplacian Kernels for Object Classification from a Single Example
Classification with only one labeled example per class is a challenging problem in machine learning and pattern recognition. While there have been some attempts to address this pr...
Hong Chang, Dit-Yan Yeung
UAI
2004
13 years 10 months ago
The Minimum Information Principle for Discriminative Learning
Exponential models of distributions are widely used in machine learning for classification and modelling. It is well known that they can be interpreted as maximum entropy models u...
Amir Globerson, Naftali Tishby
AAAI
2000
13 years 10 months ago
Restricted Bayes Optimal Classifiers
We introduce the notion of restricted Bayes optimal classifiers. These classifiers attempt to combine the flexibility of the generative approach to classification with the high ac...
Simon Tong, Daphne Koller
ICIP
2004
IEEE
14 years 10 months ago
Advances in texture analysis-energy dominant component & multiple hypothesis testing
Modelling textured images as AM-FM functions has been applied during the last years to texture analysis and segmentation tasks. In this paper we present some advances in two direc...
Iasonas Kokkinos, Georgios Evangelopoulos, Petros ...