Dimensionality reduction is an important pre-processing step for many applications. Linear Discriminant Analysis (LDA) is one of the well known methods for supervised dimensionali...
We describe a framework for decomposing the distortion between two images into a linear combination of components. Unlike conventional linear bases such as those in Fourier or wav...
To analyze the linear correlations of numeric attributes of government data, this paper proposes a method based on the clustering algorithm. A clustering method is adopted to prun...
Abstract. We present a static analysis technique for modeling and approximating the long-run resource usage of programs. The approach is based on a quantitative semantic framework ...
David Cachera, Thomas P. Jensen, Arnaud Jobin, Pas...
Two Dimensional Linear Discriminant Analysis (2DLDA) has received much interest in recent years. However, 2DLDA could make pairwise distances between any two classes become signiï...