2014 IEEE Symposium on Computational Intelligence and Ensemble Learning

The symposium topics include, but are not limited to: 1 Ensemble of evolutionary algorithms Parameter and operator ensembles for evolutionary algorithms Hyper-heuristics Portfolio of algorithms and multi-method search Ensemble of evolutionary algorithms for optimization scenarios such as multi-objective, combinatorial, constrained, etc. Hybridization of evolutionary algorithms with other search methods & ensemble methods 2 Fuzzy ensemble clustering Fuzzy ensemble classifiers and fuzzy ensemble predictors Fuzzy ensemble feature selection/dimensionality reduction Aggregation operators for fuzzy ensemble methods Rough Set based ensemble clustering and classification Type-2 Fuzzy ensemble clustering and classification 3 Ensemble methods such as boosting, bagging, random forests, multiple classifier systems, mixture of experts, multiple kernels, etc. Ensemble methods for regression, classification, clustering, ranking, feature selection, prediction, etc. Issues such as selection of constituent models, fusion and diversity of models in an ensemble, etc. 4. Hybridization of computational intelligence ensemble systems 5. Applications of ensemble of computational intelligence methods in any field