Process variations in modern VLSI technologies are growing in both magnitude and dimensionality. To assess performance variability, complex simulation and performance models param...
The reduction of dynamic systems has a rich history, with many important applications related to stability, control and verification. Reduction of nonlinear systems is typically p...
Paulo Tabuada, Aaron D. Ames, A. Agung Julius, Geo...
Abstract. There has been growing interest in developing nonlinear dimensionality reduction algorithms for vision applications. Although progress has been made in recent years, conv...
Recently the problem of dimensionality reduction has received a lot of interests in many fields of information processing. We consider the case where data is sampled from a low d...
Dimensionality reduction is a statistical tool commonly used to map high-dimensional data into lower a dimensionality. The transformed data is typically more suitable for regressi...
Bill Kapralos, Nathan Mekuz, Agnieszka Kopinska, S...