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BMCBI
2011
14 years 3 months ago
To aggregate or not to aggregate high-dimensional classifiers
Background: High-throughput functional genomics technologies generate large amount of data with hundreds or thousands of measurements per sample. The number of sample is usually m...
Cheng-Jian Xu, Huub C. J. Hoefsloot, Age K. Smilde
CVPR
2007
IEEE
16 years 1 months ago
Learning Object Material Categories via Pairwise Discriminant Analysis
In this paper, we investigate linear discriminant analysis (LDA) methods for multiclass classification problems in hyperspectral imaging. We note that LDA does not consider pairwi...
Zhouyu Fu, Antonio Robles-Kelly
ICIAR
2004
Springer
15 years 5 months ago
Learning an Information Theoretic Transform for Object Detection
We present an information theoretic approach for learning a linear dimension reduction transform for object classification. The theoretic guidance of the approach is that the trans...
Jianzhong Fang, Guoping Qiu
ICIP
2009
IEEE
14 years 9 months ago
Efficient reduction of support vectors in kernel-based methods
Kernel-based methods, e.g., support vector machine (SVM), produce high classification performances. However, the computation becomes time-consuming as the number of the vectors su...
Takumi Kobayashi, Nobuyuki Otsu
ICCV
2009
IEEE
16 years 4 months ago
Max-Margin Additive Classifiers for Detection
We present methods for training high quality object detectors very quickly. The core contribution is a pair of fast training algorithms for piece-wise linear classifiers, which ...
Subhransu Maji, Alexander C. Berg