We investigate some approaches to solving nonconvex global optimization problems by convex nonlinear programming methods. We assume that the problem becomes convex when selected va...
Learning from ambiguous training data is highly relevant in many applications. We present a new learning algorithm for classification problems where labels are associated with se...
This paper introduces a new representation for planar curves. From the well-known Dirichlet problem for a disk, the harmonic function embedded in a circular disk is solely depende...
Sang-Mook Lee, A. Lynn Abbott, Neil A. Clark, Phil...
We present a probabilistic analysis for a large class of combinatorial optimization problems containing, e.g., all binary optimization problems defined by linear constraints and a...
We propose a new approach to estimate the joint spectral radius and the joint spectral subradius of an arbitrary set of matrices. We first restrict our attention to matrices that ...