Call For Papers Special Session: Evolutionary Feature Reduction The 10th International Conference on Simulated Evolution And Learning (SEAL 2014)

Call For Papers
Special Session: Evolutionary Feature Reduction
The 10th International Conference on Simulated Evolution And Learning (SEAL 2014)
15-18 December 2014, Dunedin, New Zealand
http://seal2014.otago.ac.nz/

================

Large numbers of features/attributes are often problematic in machine learning and data mining. They lead to conditions known as “the cures of dimensionality”. Feature reduction aims to solve this problem by selecting a small number of original features or constructing a smaller set of new features. Feature selection and construction are challenging tasks due to the large search space and feature interaction problems. Recently, there has been increasing interest in using evolutionary computation approaches to solve these problems.

The theme of this special session is the use of evolutionary computation for feature reduction, covering ALL different evolutionary computation paradigms including evolutionary algorithms, swarm intelligence, learning classifier systems, harmony search, artificial immune systems, and cross-fertilization of evolutionary computation and other techniques such as neural networks, and fuzzy and rough sets. This special session aims to investigate both the new theories and methods in different evolutionary computation paradigms to feature reduction, and the applications of evolutionary computation for feature reduction. Authors are invited to submit their original and unpublished work to this special session.
Topics of interest include but are not limited to:
• Feature ranking/weighting
• Feature subset selection
• Dimensionality reduction
• Feature construction
• Filter, wrapper, and embedded feature selection
• Hybrid feature selection
• Feature reduction for both supervised and unsupervised learning
• Multi-objective feature reduction
• Feature reduction with imbalanced data
• Analysis on evolutionary feature reduction methods
• Real-world applications of evolutionary feature reduction, e.g. gene analysis, bio-marker detection, et al.
================
Important Dates:
28 July 2014, deadline for submission of full papers (<=12 pages)
29 August 2014, Notification of acceptance
16 September 2014, Deadline for camera-ready copies of accepted papers
15-18 December 2014, Conference sessions (including tutorials and workshops)
================
Paper Submission:
You should follow the SEAL 2014 Submission Web Site
(http://seal2014.otago.ac.nz/submissions.aspx). In the Main Research Topic, please choose
“Evolutionary Feature Reduction”
Special session papers are treated the same as regular conference papers. All papers will be fully refereed by a minimum of two specialized referees. Before final acceptance, all referees comments must be considered. All accepted papers that are presented at the conference will be included in the conference proceedings, to be published in Lecture Notes in Computer Science (LNCS) by Springer. Selected papers will be invited for further revision and extension for possible publication in a special issue of a SCI journal after further review Soft Computing (Springer, Impact Factor 1.124).
================
Special Session Organizers:
Dr Bing Xue
School of Engineering and Computer Science, Victoria University of Wellington,
PO Box 600, Wellington, New Zealand.
Email: bing.xue@ecs.vuw.ac.nz
Homepage: http://ecs.victoria.ac.nz/Main/BingXue

Dr Kourosh Neshatian
Computer Science and Software Engineering, College of Engineering, University of Canterbury
Email: kourosh.neshatian@canterbury.ac.nz
Homepage: http://www.cosc.canterbury.ac.nz/kourosh.neshatian/
================
Note: Please reply to me if you want to be a Program Committee Member.

Best regards,
Bing

***************************************
Room CO 351, Cotton Building
Victoria University of Wellington
PO Box 600, Wellington 6140,
New Zealand
Mobile Phone; +64 220327481
Phone: +64-4-463 5233+ext 8874
Email: xuebingfifa@gmail.com
Bing.Xue@ecs.vuw.ac.nz
****************************************

Leave a Reply

Your email address will not be published. Required fields are marked *

This site uses Akismet to reduce spam. Learn how your comment data is processed.