We continue the study of the trade-off between the length of PCPs and their query complexity, establishing the following main results (which refer to proofs of satisfiability of c...
Eli Ben-Sasson, Oded Goldreich, Prahladh Harsha, M...
The perceptron algorithm, developed mainly in the machine learning literature, is a simple greedy method for finding a feasible solution to a linear program (alternatively, for le...
This paper addresses the problem of piecewise linear approximation of implicit surfaces. We first give a criterion ensuring that the zero-set of a smooth function and the one of a...
Jean-Daniel Boissonnat, David Cohen-Steiner, Gert ...
In this paper we present a sublinear time (1+ )-approximation randomized algorithm to estimate the weight of the minimum spanning tree of an n-point metric space. The running time...
: We initiate the study of a new measure of approximation. This measure compares the performance of an approximation algorithm to the random assignment algorithm. This is a useful ...