This paper demonstrates the applicability of the recently proposed supervised dimension reduction, hierarchical linear discriminant analysis (h-LDA) to a well-known spatial locali...
Abstract--High-dimensional data are common in many domains, and dimensionality reduction is the key to cope with the curse-of-dimensionality. Linear discriminant analysis (LDA) is ...
The flip-chip package provides a high chip-density solution to the demand for more I/O pads of VLSI designs. In this paper, we present the first routing algorithm in the literatur...
Bayesian Kullback Ying—Yang dependence reduction system and theory is presented. Via stochastic approximation, implementable algorithms and criteria are given for parameter lear...
We consider parallel algorithms for computing the Hermite normal form of matrices over Euclidean rings. We use standard types of reduction methods which are the basis of many algor...