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The expected improvement algorithm (or efficient global optimization) aims for global continuous optimization with a limited budget of black-box function evaluations. It is based on a statistical model of the function learned from previous evaluations and an infill criterion the expected improvement-used to find a promising point for a new evaluation. The(More)
Expected improvement algorithms are commonly used in global optimization problems where evaluating the objective function is costly. The Expected Hypervolume Improvement (EHVI) is a recent generalization of these algorithms to multiobjective optimization. The computation of the EHVI is based on a multidimensional integration of a piecewise defined nonlinear(More)
In this thesis we investigate how to automatically identify the prominent actors in social networks, so that they can for instance be targeted for viral marketing. To do this, we look at characteristics of the friendship graph and apply data mining methods from the Weka toolkit. We compare the set of nodes resulting from these methods with a set of nodes(More)
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