114 search results - page 12 / 23 » Feature Subset Selection and Ranking for Data Dimensionality... |
102
Voted
ICIP
2000
IEEE
16 years 3 months ago
2000
IEEE
In many Earth observation missions, a large amount of data is collected by the on-board sensors, and must be transmitted to ground through a channel with limited capacity; in this...
140
Voted
TSP
2011
14 years 8 months ago
2011
—This work proposes a blind adaptive reduced-rank scheme and constrained constant-modulus (CCM) adaptive algorithms for interference suppression in wireless communications system...
140
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SAC
2008
ACM
15 years 1 months ago
2008
ACM
A major obstacle that decreases the performance of text classifiers is the extremely high dimensionality of text data. To reduce the dimension, a number of approaches based on rou...
133
Voted
SDM
2007
SIAM
15 years 3 months ago
2007
SIAM
Manifold learning is an effective methodology for extracting nonlinear structures from high-dimensional data with many applications in image analysis, computer vision, text data a...
112
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SDM
2010
SIAM
15 years 8 days ago
2010
SIAM
A popular approach for dimensionality reduction and data analysis is principal component analysis (PCA). A limiting factor with PCA is that it does not inform us on which of the o...