The construction of low-dimensional models explaining highdimensional signal observations provides concise and efficient data representations. In this paper, we focus on pattern ...
Existing value function approximation methods have been successfully used in many applications, but they often lack useful a priori error bounds. We propose a new approximate bili...
We provide a new comparison between hexagonal and orthogonal lattices, based on approximation theory. For each of the lattices, we select the "natural" spline basis func...
—We introduce a new tool for approximation and testing algorithms called partitioning oracles. We develop methods for constructing them for any class of bounded-degree graphs wit...
Avinatan Hassidim, Jonathan A. Kelner, Huy N. Nguy...
Abstract. We provide improved approximation algorithms for the minmax generalization problems considered by Du, Eppstein, Goodrich, and Lueker [1]. In min-max generalization proble...