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PR
2008
129views more  PR 2008»
13 years 7 months ago
A comparison of generalized linear discriminant analysis algorithms
7 Linear discriminant analysis (LDA) is a dimension reduction method which finds an optimal linear transformation that maximizes the class separability. However, in undersampled p...
Cheong Hee Park, Haesun Park
TKDE
2011
479views more  TKDE 2011»
13 years 2 months ago
Learning Semi-Riemannian Metrics for Semisupervised Feature Extraction
—Discriminant feature extraction plays a central role in pattern recognition and classification. Linear Discriminant Analysis (LDA) is a traditional algorithm for supervised feat...
Wei Zhang, Zhouchen Lin, Xiaoou Tang
JAVA
2001
Springer
14 years 5 days ago
Supporting dynamic parallel object arrays
We present efficient support for generalized arrays of parallel data driven objects. Array elements are regular C++ objects, and are scattered across the parallel machine. An indi...
Orion Sky Lawlor, Laxmikant V. Kalé
HPDC
2000
IEEE
14 years 4 days ago
Event Services for High Performance Computing
The Internet and the Grid are changing the face of high performance computing. Rather than tightly-coupled SPMD-style components running in a single cluster, on a parallel machine...
Greg Eisenhauer, Fabián E. Bustamante, Kars...
VAMOS
2010
Springer
13 years 9 months ago
Using Collaborations to Encapsulate Features? An Explorative Study
A feature is a program characteristic visible to an end-user. Current research strives to encapsulate the implementation of a feature in a module. Jak is a language extension to Ja...
Martin Kuhlemann, Norbert Siegmund, Sven Apel