: Laplacian Linear Discriminant Analysis (LapLDA) and Semi-supervised Discriminant Analysis (SDA) are two recently proposed LDA methods. They are developed independently with the a...
Graph construction plays a key role on learning algorithms based on graph Laplacian. However, the traditional graph construction approaches of -neighborhood and k-nearest-neighbor...
— Over the last century, Component Analysis (CA) methods such as Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), Canonical Correlation Analysis (CCA), Lap...
Abstract. The study of natural image statistics considers the statistical properties of large collections of images from natural scenes, and has applications in image processing, c...
Given a large, real graph, how can we generate a synthetic graph that matches its properties, i.e., it has similar degree distribution, similar (small) diameter, similar spectrum,...