in Proc. IEEE Int’l Conf. on Image Processing (ICIP), pp 889-892, 2006 Traditional iterative tomographic reconstruction methods resort to gradient decent methods and require sig...
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...
We compare the convergence performance of different numerical schemes for computing the fundamental matrix from point correspondences over two images. First, we state the problem ...
Abstract. Reinforcement learning (RL) is a widely used learning paradigm for adaptive agents. There exist several convergent and consistent RL algorithms which have been intensivel...
Lucian Busoniu, Damien Ernst, Bart De Schutter, Ro...