502 search results - page 27 / 101 » Principal Component Analysis for Sparse High-Dimensional Dat... |
109
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ICANN
2009
Springer
15 years 7 months ago
2009
Springer
In this paper the sparse coding principle is employed for the representation of multimodal image data, i.e. image intensity and range. We estimate an image basis for frontal face i...
127
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JMLR
2012
13 years 2 months ago
2012
We develop a high dimensional nonparametric classification method named sparse additive machine (SAM), which can be viewed as a functional version of support vector machine (SVM)...
102
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JMLR
2010
14 years 11 months ago
2010
Sparse coding—that is, modelling data vectors as sparse linear combinations of basis elements—is widely used in machine learning, neuroscience, signal processing, and statisti...
124
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ICCV
2011
IEEE
14 years 14 days ago
2011
IEEE
Linear subspace learning (LSL) is a popular approach to image recognition and it aims to reveal the essential features of high dimensional data, e.g., facial images, in a lower di...
118
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BMCBI
2010
15 years 17 days ago
2010
Background: Visualization of DNA microarray data in two or three dimensional spaces is an important exploratory analysis step in order to detect quality issues or to generate new ...