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» The Generalized Dimensionality Reduction Problem
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CVPR
2008
IEEE
15 years 26 days ago
A unified framework for generalized Linear Discriminant Analysis
Linear Discriminant Analysis (LDA) is one of the wellknown methods for supervised dimensionality reduction. Over the years, many LDA-based algorithms have been developed to cope w...
Shuiwang Ji, Jieping Ye
PAMI
2011
13 years 5 months ago
Multiple Kernel Learning for Dimensionality Reduction
—In solving complex visual learning tasks, adopting multiple descriptors to more precisely characterize the data has been a feasible way for improving performance. The resulting ...
Yen-Yu Lin, Tyng-Luh Liu, Chiou-Shann Fuh
SMA
2003
ACM
173views Solid Modeling» more  SMA 2003»
14 years 4 months ago
Automating the CAD/CAE dimensional reduction process
Dimensional reduction is a simplification technique that eliminates one or more dimensions from a boundary value problem. It results in significant computational savings with mini...
Krishnan Suresh
ICDE
2002
IEEE
91views Database» more  ICDE 2002»
14 years 3 months ago
Lossy Reduction for Very High Dimensional Data
We consider the use of data reduction techniques for the problem of approximate query answering. We focus on applications for which accurate answers to selective queries are requi...
Chris Jermaine, Edward Omiecinski
ICML
2007
IEEE
14 years 11 months ago
A transductive framework of distance metric learning by spectral dimensionality reduction
Distance metric learning and nonlinear dimensionality reduction are two interesting and active topics in recent years. However, the connection between them is not thoroughly studi...
Fuxin Li, Jian Yang, Jue Wang