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...
—Discriminant feature extraction plays a central role in pattern recognition and classification. Linear Discriminant Analysis (LDA) is a traditional algorithm for supervised feat...
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...
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...
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...