This paper considers constraint propagation methods for continuous constraint satisfaction problems consisting of linear and quadratic constraints. All methods can be applied after...
Abstract. In stochastic programming and decision analysis, an important issue consists in the approximate representation of the multidimensional stochastic underlying process in th...
Kristina Sutiene, Dalius Makackas, Henrikas Pranev...
Abstract. We study the application of limited-width MDDs (multivalued decision diagrams) as discrete relaxations for combinatorial optimization problems. These relaxations are used...
David Bergman, Willem Jan van Hoeve, John N. Hooke...
In this paper we address the problem of pool based active learning, and provide an algorithm, called UPAL, that works by minimizing the unbiased estimator of the risk of a hypothe...
The standard language for describing the asymptotic behavior of algorithms is theoretical computational complexity. We propose a method for describing the asymptotic behavior of p...
Simon Goldsmith, Alex Aiken, Daniel Shawcross Wilk...