An ensemble is a set of learned models that make decisions collectively. Although an ensemble is usually more accurate than a single learner, existing ensemble methods often tend ...
Modern computer systems are called on to deal with billions of events every second, whether they are instructions executed, memory locations accessed, or packets forwarded. This p...
ion of a given partial assignment of values to variables. Compared with other symmetry breaking techniques, the big advantage of dynamic symmetry breaking is that it can accommodat...
Current numerical model checkers for stochastic systems can efficiently analyse stochastic models. However, the fact that they are unable to provide debugging information constrain...
Abstract. We explore a new general-purpose heuristic for nding highquality solutions to hard optimization problems. The method, called extremal optimization, is inspired by self-or...
Stefan Boettcher, Allon G. Percus, Michelangelo Gr...