Code generation for embedded processors creates opportunities for several performance optimizations not applicable for traditional compilers. We present techniques for improving d...
Preeti Ranjan Panda, Nikil D. Dutt, Alexandru Nico...
A generalized or tunable-kernel model is proposed for probability density function estimation based on an orthogonal forward regression procedure. Each stage of the density estimat...
Background: Growing interest on biological pathways has called for new statistical methods for modeling and testing a genetic pathway effect on a health outcome. The fact that gen...
In this paper, we propose a method for robust kernel density estimation. We interpret a KDE with Gaussian kernel as the inner product between a mapped test point and the centroid ...
The Support Vector Machine (SVM) has emerged in recent years as a popular approach to the classification of data. One problem that faces the user of an SVM is how to choose a kerne...