We study nonparametric regression between Riemannian manifolds based on regularized empirical risk minimization. Regularization functionals for mappings between manifolds should re...
We study an extension of the "standard" learning models to settings where observing the value of an attribute has an associated cost (which might be different for differ...
We propose a new approach to recover epipolar geometry from a pair of uncalibrated images. By minimizing a proposed cost function, our approach matches the detected feature points...
We give a polynomial approximation scheme for the problem of scheduling on uniformly related parallel machines for a large class of objective functions that depend only on the mac...
Abstract. The paper presents an algorithm for identifying the independent subspace analysis model based on source dynamics. We propose to separate subspaces by decoupling their dyn...