We consider layouting news articles on a page as a cutting and packing problem with output maximization. We propose to tailor news articles by employing automatic summarization to...
A common approach for dealing with large data sets is to stream over the input in one pass, and perform computations using sublinear resources. For truly massive data sets, howeve...
Jon Feldman, S. Muthukrishnan, Anastasios Sidiropo...
Stochastic optimization problems attempt to model uncertainty in the data by assuming that (part of) the input is specified in terms of a probability distribution. We consider the...
We consider a fundamental problem in computational learning theory: learning an arbitrary Boolean function which depends on an unknown set of k out of n Boolean variables. We give...
Elchanan Mossel, Ryan O'Donnell, Rocco A. Servedio
We study the problem of factoring univariate polynomials over finite fields. Under the assumption of the Extended Riemann Hypothesis (ERH), Gao [Gao01] designed a polynomial time ...