We present a globally convergent method for regularized risk minimization problems. Our method applies to Support Vector estimation, regression, Gaussian Processes, and any other ...
A general scheme for trust-region methods on Riemannian manifolds is proposed and analyzed. Among the various approaches available to (approximately) solve the trust-region subpro...
Pierre-Antoine Absil, C. G. Baker, Kyle A. Galliva...
Abstract-- Switched systems evolve over a sequence of continuous modes of operation, transitioning between modes in a discrete manner. Assuming a mode sequence is known, the evolut...
In this paper, we propose a novel non-parametric clustering method based on non-parametric local shrinking. Each data point is transformed in such a way that it moves a specific ...
Manydesign problems are solved using multiple levels of abstraction, wherea design at one level has combinatorially manychildren at the next level. A stochastic optimization metho...
Louis I. Steinberg, J. Storrs Hall, Brian D. Davis...