A formalism for expressing the operational semantics of proof languages used in procedural theorem provers is proposed. It is argued that this formalism provides an elegant way to...
Recent work on geometric vision problems has exploited convexity properties in order to obtain globally optimal solutions. In this paper we give an overview of these developments a...
This paper proposes robust algorithms to deconvolve discrete noised signals and images. The solutions are derived as linear combinations of spline wavelet packets that minimize so...
Amir Averbuch, Valery A. Zheludev, Pekka Neittaanm...
We present a new sparse Gaussian Process (GP) model for regression. The key novel idea is to sparsify the spectral representation of the GP. This leads to a simple, practical algo...
We study the problem of image denoising where images are assumed to be samples from low dimensional (sub)manifolds. We propose the algorithm of locally linear denoising. The algor...