In this paper we propose a new algorithm for learning polyhedral classifiers. In contrast to existing methods for learning polyhedral classifier which solve a constrained optimiza...
This paper presents a new framework that integrates relevance feedback into region-based image retrieval (RBIR) systems based on radial basis function network (RBFN). A modified u...
Digital subtraction is a promising technique used in radiographic studies of periapical lesions and other dental disorders for which the treatment must be evaluated over time. Thi...
Earlier research has shown that the problem of optimal weighted median filtering with structural constraints can be formulated as a nonconvex nonlinear programming problem in gene...
Abstract. We propose a unifying framework for polyhedral approximation in convex optimization. It subsumes classical methods, such as cutting plane and simplicial decomposition, bu...