Background: Bioinformatics data analysis toolbox needs general-purpose, fast and easily interpretable preprocessing tools that perform data integration during exploratory data ana...
This paper presents a Local Learning Projection (LLP) approach for linear dimensionality reduction. We first point out that the well known Principal Component Analysis (PCA) essen...
Dimensionality reduction is the problem of finding a low-dimensional representation of highdimensional input data. This paper examines the case where additional information is kno...
Process variations in modern VLSI technologies are growing in both magnitude and dimensionality. To assess performance variability, complex simulation and performance models param...
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...