Connectionists: CIEL 2016: Ensemble Learning Symposium in SSCI 2016 in Greece

[Ponnuthurai Nagaratnam Suganthan]

http://ssci2016.cs.surrey.ac.uk/
Final Extended Paper Submission Deadline:  15th August 2016
2016 IEEE Symposium on Computational Intelligence and Ensemble Learning (IEEE CIEL'2016)

Ensemble learning attempts to enhance the performance of systems (clustering, classification, prediction, feature selection, search, optimization, rule extraction, etc.) by using multiple models instead of using a single model. This approach is intuitively meaningful as a single model may not always be the best for solving a complex problem while multiple models are more likely to yield results better than each of the constituent models. Although in the past, ensemble methods have been mainly studied in the context of classification and time series prediction, recently they are being used in algorithms in other scenarios such as clustering, fuzzy systems, evolutionary algorithms, dimensionality reduction and so on.

The aim of this symposium is to bring together researchers and practitioners who are working in the overlapping fields of ensemble methods and Machine Learning. Papers dealing with theory, algorithms, analysis, and applications of ensemble of computational intelligence methods are sought for this symposium.

Scopes and Topics

The symposium topics include, but are not limited to:

  *
     *   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.
  *      Hybridization of computational intelligence ensemble systems
  *     Applications of ensemble of computational intelligence methods in any field

Organisers
P. N. Suganthan
Nanyang Technological University, Singapore. Email:epnsugan at ntu.edu.sg
Nikhil R Pal
Indian Statistical Institute, Calcutta, India. Email:nikhil at isical.ac.in
Xin Yao
University of Birmingham, UK. Email:x.yao at cs.bham.ac.uk
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