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CVPR
2007
IEEE
14 years 9 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
CVPR
2008
IEEE
14 years 9 months ago
Margin-based discriminant dimensionality reduction for visual recognition
Nearest neighbour classifiers and related kernel methods often perform poorly in high dimensional problems because it is infeasible to include enough training samples to cover the...
Hakan Cevikalp, Bill Triggs, Frédéri...
SIGIR
2006
ACM
14 years 1 months ago
Large scale semi-supervised linear SVMs
Large scale learning is often realistic only in a semi-supervised setting where a small set of labeled examples is available together with a large collection of unlabeled data. In...
Vikas Sindhwani, S. Sathiya Keerthi
CVPR
2010
IEEE
13 years 5 months ago
Visual classification with multi-task joint sparse representation
We address the problem of computing joint sparse representation of visual signal across multiple kernel-based representations. Such a problem arises naturally in supervised visual...
Xiaotong Yuan, Shuicheng Yan
PRL
2007
101views more  PRL 2007»
13 years 7 months ago
Accuracy versus speed in context-based object detection
The visual detection and recognition of objects is facilitated by context. This paper studies two types of learning methods for realizing context-based object detection in paintin...
Niek Bergboer, Eric O. Postma, H. Jaap van den Her...