This paper formulates the problem of object categorization in the discriminant analysis framework focusing on transforming visual feature data so as to make it conform to the comp...
A convenient way of analysing Riemannian manifolds is to embed them in Euclidean spaces, with the embedding typically obtained by flattening the manifold via tangent spaces. This...
The quadratic discriminant (QD) classifier has proved to be simple and effective in many pattern recognition problems. However, it requires the computation of the inverse of the sa...
Abstract. Most real-world datasets are, to a certain degree, skewed. When considered that they are also large, they become the pinnacle challenge in data analysis. More importantly...
—This paper presents a novel methodology for social network discovery based on the sensitivity coefficients of importance metrics, namely the Markov centrality of a node, a metr...