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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 computational intelligence. 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:

Special Sessions

All special session proposals containing a title of the special session, to which symposium it is proposed to, names, affiliations and email addresses of proposers, together with a description of aims and scope of the special session and a list of 6-10 potential contributors, should be sent to hisaoi@cs.osakafu-u.ac.jp.

Further information about special session proposals and a list of accepted special sessions can be found at:http://ssci2016.cs.surrey.ac.uk/Special%20Sessions.htm

Organisers

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

Program Committee
(To be finalised)