There has been significant interest lately in the task of constructing codes that are testable with a small number of random probes. Ben-Sasson and Sudan show that the repeated te...
Abstract. We give a generic construction of an optimal hitting set generator (HSG) from any good “reconstructive” disperser. Past constructions of optimal HSGs have been based ...
We resolve two open problems presented in [8]. First, we consider the problem of reconstructing an unknown string T over a fixed alphabet using queries of the form “does the st...
The field of stochastic optimization studies decision making under uncertainty, when only probabilistic information about the future is available. Finding approximate solutions to...
Traditionally, a fundamental assumption in evaluating the performance of algorithms for sorting and selection has been that comparing any two elements costs one unit (of time, work...
Optimal dispersers have better dependence on the error than optimal extractors. In this paper we give explicit disperser constructions that beat the best possible extractors in so...
Ronen Gradwohl, Guy Kindler, Omer Reingold, Amnon ...
We introduce a “derandomized” analogue of graph squaring. This operation increases the connectivity of the graph (as measured by the second eigenvalue) almost as well as squar...
Abstract. In this paper we introduce a new technique for approximation schemes for geometrical optimization problems. As an example problem, we consider the following variant of th...
A caterpillar is a tree in which all vertices of degree three or more lie on one path, called the backbone. We present a polynomial time algorithm that produces a linear arrangeme...