332 search results - page 9 / 67 » On the Performance of Chernoff-Distance-Based Linear Dimensi... |
ICCV
2007
IEEE
15 years 3 months ago
2007
IEEE
Dimensionality reduction plays a fundamental role in data processing, for which principal component analysis (PCA) is widely used. In this paper, we develop the Laplacian PCA (LPC...
ICML
2005
IEEE
15 years 10 months ago
2005
IEEE
Given a classification problem, our goal is to find a low-dimensional linear transformation of the feature vectors which retains information needed to predict the class labels. We...
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ICML
2006
IEEE
15 years 10 months ago
2006
IEEE
Clustering is one of the most widely used statistical tools for data analysis. Among all existing clustering techniques, k-means is a very popular method because of its ease of pr...
UM
2009
Springer
15 years 4 months ago
2009
Springer
Abstract. Words mean different things to different people, and capturing these differences is often a subtle art. These differences are often “a matter of perspective,” and...
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WEBI
2010
Springer
14 years 7 months ago
2010
Springer
High-dimensional data usually incur learning deficiencies and computational difficulties. We present a novel semi-supervised dimensionality reduction technique that embeds high-dim...