74 search results - page 4 / 15 » Nonlinear dimensionality reduction for classification using ... |
CIKM
2008
Springer
13 years 7 months ago
2008
Springer
Finding latent patterns in high dimensional data is an important research problem with numerous applications. The most well known approaches for high dimensional data analysis are...
BMCBI
2006
13 years 5 months ago
2006
Background: Accurate methods for extraction of meaningful patterns in high dimensional data have become increasingly important with the recent generation of data types containing ...
ICCV
2007
IEEE
14 years 2 days 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...
AAAI
2007
13 years 8 months ago
2007
Recently the problem of dimensionality reduction has received a lot of interests in many fields of information processing. We consider the case where data is sampled from a low d...
ICASSP
2011
IEEE
12 years 9 months ago
2011
IEEE
This paper presents a novel method for reducing the dimensionality of kernel spaces. Recently, to maintain the convexity of training, loglinear models without mixtures have been u...