Many critical decisions for individuals and organizations are often framed as preferential choices: the process of selecting the best option out of a set of alternatives. This pap...
Genetic algorithms (GAs) have been applied previously to UML-driven, stress test requirements generation with the aim of increasing chances of discovering faults relating to networ...
We present initial results from the first empirical evaluation of a graph partitioning algorithm inspired by the Arora-Rao-Vazirani algorithm of [5], which combines spectral and ...
Kevin J. Lang, Michael W. Mahoney, Lorenzo Orecchi...
In this paper we perform an empirical evaluation of supervised learning on highdimensional data. We evaluate performance on three metrics: accuracy, AUC, and squared loss and stud...
In empirical studies of Evolutionary Algorithms, it is usually desirable to evaluate and compare algorithms using as many different parameter settings and test problems as possible...