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CVPR
2007
IEEE
14 years 12 months ago
Feature Extraction by Maximizing the Average Neighborhood Margin
A novel algorithm called Average Neighborhood Margin Maximization (ANMM) is proposed for supervised linear feature extraction. For each data point, ANMM aims at pulling the neighb...
Fei Wang, Changshui Zhang
ICCV
2007
IEEE
14 years 11 months ago
Classification of Weakly-Labeled Data with Partial Equivalence Relations
In many vision problems, instead of having fully labeled training data, it is easier to obtain the input in small groups, where the data in each group is constrained to be from th...
Sanjiv Kumar, Henry A. Rowley
ICCV
2007
IEEE
14 years 11 months ago
Semi-supervised Discriminant Analysis
Linear Discriminant Analysis (LDA) has been a popular method for extracting features which preserve class separability. The projection vectors are commonly obtained by maximizing ...
Deng Cai, Xiaofei He, Jiawei Han
ICCV
2001
IEEE
14 years 11 months ago
Lambertian Reflectance and Linear Subspaces
We prove that the set of all Lambertian reflectance functions (the mapping from surface normals to intensities) obtained with arbitrary distant light sources lies close to a 9D lin...
Ronen Basri, David W. Jacobs
ECCV
2006
Springer
14 years 11 months ago
Extending Kernel Fisher Discriminant Analysis with the Weighted Pairwise Chernoff Criterion
Many linear discriminant analysis (LDA) and kernel Fisher discriminant analysis (KFD) methods are based on the restrictive assumption that the data are homoscedastic. In this paper...
Guang Dai, Dit-Yan Yeung, Hong Chang