We study nonparametric regression between Riemannian manifolds based on regularized empirical risk minimization. Regularization functionals for mappings between manifolds should re...
Abstract. We propose an algorithmic framework for computing global solutions of variational models with convex regularity terms that permit quite arbitrary data terms. While the mi...
Thomas Pock, Daniel Cremers, Horst Bischof, Antoni...
This paper presents a complete framework for attention-based video streaming for low bandwidth networks. First, motivated by the fovea-periphery distinction of biological vision s...
Classification of brain images obtained through functional magnetic resonance imaging (fMRI) poses a serious challenge to pattern recognition and machine learning due to the extrem...
The objective of this paper is twofold. The first part provides further insight in the statistical properties of the Welch power spectrum estimator. A major drawback of the Welch m...