We present a new algorithm for learning a convex set in n-dimensional space given labeled examples drawn from any Gaussian distribution. The complexity of the algorithm is bounded ...
Abstract. We present a multigrid algorithm for the solution of distributed parameter inverse problems constrained by variable-coefficient linear parabolic partial differential equa...
This paper characterizes the polynomial time learnability of TPk, the class of collections of at most k rst-order terms. A collection in TPk denes the union of the languages den...
We describe a simple randomized construction for generating pairs of hash functions h1, h2 from a universe U to ranges V = [m] = {0, 1, . . . , m - 1} and W = [m] so that for ever...
Nonlinear approximation has usually been studied under deterministic assumptions and complete information about the underlying functions. In the present paper we assume only partia...