Titlebook: Learning and Intelligent Optimization; 7th International Co Giuseppe Nicosia,Panos Pardalos Conference proceedings 2013 Springer-Verlag Ber

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MOCA-I: Discovering Rules and Guiding Decision Maker in the Context of Partial Classification in Lahm adapted to large and imbalanced datasets, as encountered in hospital data. We associate to this algorithm an original post-processing method based on ROC curve to help the decision maker to choose the most interesting rules. After an introduction to problems brought by hospital data such as class

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Fast Computation of the Multi-Points Expected Improvement with Applications in Batch Selection, new way of computing .-EI, without using Monte-Carlo simulations, through a closed-form formula. The latter allows a very fast computation of .-EI for reasonably low values of . (typically, less than 10). New parallel kriging-based optimization strategies, tested on different toy examples, show pro

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R2-EMOA: Focused Multiobjective Search Using R2-Indicator-Based Selection,or as the secondary selection criterion. First experiments indicate that the R2-EMOA accurately approximates the Pareto front of the considered continuous multiobjective optimization problems. Furthermore, decision makers’ preferences can be included by adjusting the weight vector distributions of t

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Multi-Objective Optimization for Relevant Sub-graph Extraction,that have been introduced fall into graph clustering. In this paper, a novel trend of relevant sub-graphs extraction problem was considered as multi-objective optimization. Genetic Algorithms (GAs) and Simulated Annealing (SA) were then used to solve the problem applied to biological networks. Compa