Task Force Proposal

Proposed Name: Evolutionary Computation for Feature Selection and Construction

Scope:

Many real-world problems involve a large number of features/variables, which leads to the problem known as “the curse of dimensionality". However, not all features are essential since many of them are redundant or irrelevant, and the useful features are typically not equally important. This problem can be solved by feature selection to select a small subset of original features, or feature construction to construct a smaller set of high-level features using the original low-level features and mathematical or logical operators. Feature selection and construction are challenging tasks because of the large search space and feature interaction problems. Due to the powerful search abilities and/or flexible solution encoding/representation schemes, there has been increasing interest in using evolutionary computation (EC) techniques to solve feature selection and construction problems. However, the dimensionality and the complexity of the data in real-world problems grows fast in recent years, which requires novel effective and efficient approaches to addressing new challenges in this area.

Mission:

Feature selection and construction are important tasks in many areas, such as Data Mining, Machine Learning, Image Processing and Analysis, Statistics, Operation Research, Biology, Engineering, Finance, and Business. Researchers from these areas have started investigating EC techniques to solve feature selection and construction problems, but these researchers attend different events and activities. This task force would be an outstanding platform for them to share knowledge, exchange ideas, transfer tools, and generate new research lines.

The objectives of this task force are:

  • To promote the applications of EC techniques to address feature selection and construction tasks in different areas.
  • To facilitate collaboration between researchers from related disciplines, such as Data Mining, Machine Learning,Statistics, Operation Research, Biology, Engineering, Finance, Business, Image Processing and Analysis, Classification, Clustering, Regression, Medical and Health Care, Networks, and Security.
  • To promote discussions and connections between researchers, industrialists, and practitioners.

Anticipated interests

The theme of this task force is EC for feature selection and construction, covering all different EC paradigms. Topics of interest include but are not limited to:

  • Feature ranking/weighting, subset selection and construction
  • Novel fitness evaluation criteria in feature selection and construction
  • Filter, wrapper, and embedded approaches to feature selection and construction
  • Single objective and multi-objective feature selection and construction
  • Theoretical analysis on evolutionary feature selection and construction algorithms
  • Hybridisation of EC and neural networks, and fuzzy systems for feature selection and construction
  • Hybridisation of EC and machine learning, information theory, statistics, mathematical modeling, etc., for feature selection and construction
  • Feature extraction/construction in images and video sequences
  • Feature selection and construction on high-dimensional and large-scale data
  • EC for feature selection and construction in real-world applications

Activities

Past activities:

  • Special session on Evolutionary Feature Selection and Construction in IEEE Congress on Evolutionary Computation (CEC 2015)
  • Special session on Evolutionary Feature Reduction in The Tenth International Conference on Simulated Evolution And Learning (SEAL 2014)

Future activities:

  • Organise a special session at IEEE WCCI 2016/CEC2016
  • Organise special sessions at international conferences
  • Organise journal special issues

Proposed Committee:

Chair: Dr Bing Xue

Vice Chair: Prof. Yaochu Jin, Prof. Mengjie Zhang

Members:

  • Xin Yao, UK
  • Kay Chen Tan, Singapore
  • Yew-Soon Ong, Singapore
  • Hisao Ishibuchi, Japan
  • Xiaodong Li, Australia
  • Carlos A. Coello Coello, Mexico
  • Krzysztof Krawiec, Poland
  • Sergio Damas, Spain
  • Alberto Moraglio, UK
  • Brijesh Verma, Australia
  • Zexuan Zhu, China,
  • Will Browne, New Zealand
  • Kai Qin, Australia
  • Stefano Cagnoni,Italy
  • Gustavo Olague, Mexico
  • Lin Shang, China
  • Peter Andreae, New Zealand
  • Yi Mei, Australia
  • Ke Tang, China
  • Urvesh Bhowan, Ireland
  • Kourosh Neshatian, New Zealand
  • Andy Song, Australia
  • Carlton Downey, USA
  • Liam Cervante, Google UK (Industry)

Biographies

Bing Xue is currently a Post-Doctoral Research Fellow in Evolutionary Computation Research Group at Victoria University of Wellington and leading the strategic research direction on evolutionary feature selection and construction. Her research focuses mainly on evolutionary computation, feature selection, feature construction, multi-objective optimisation, data mining and machine learning. She has nearly 40 papers published in fully referred international journals and conferences and 30 of them are on evolutionary feature selection and construction. She is currently co-supervising six PhD students and visiting scholars, and over 10 Honours and summer research projects.

Dr Xue is the chair of the special session on Evolutionary Feature Selection and Construction in IEEE Congress on Evolutionary Computation (CEC) 2015 and the chair of the special session on Evolutionary Feature Reduction in the international conference on Simulated Evolution And Learning (SEAL) 2014. She is a Guest Editor for the Special Issue on Evolutionary Feature Reduction and Machine Learning for the Springer Journal of Soft Computing. Dr Xue is serving as a reviewer of over 10 international journals including IEEE Transactions on Evolutionary Computation, IEEE Transaction on Cybernetics and Information Sciences, and many international conferences including IEEE Congress on Evolutionary Computation (CEC), International Joint Conference on Artificial Intelligence (IJCAI), Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), and International Conference on Simulated Evolution and Learning (SEAL).

Dr Xue is a member of IEEE and IEEE Computational Intelligence Society. She is also serving as the Director of Women in Engineering for the IEEE New Zealand Central Section and the Secretary of the IEEE Chapter on Computational Intelligence in that Section.

Yaochu Jin received the B.Sc., M.Sc., and Ph.D. degrees from Zhejiang University, Hangzhou, China, in 1988, 1991, and 1996 respectively, and the Dr. Ing. degree from Ruhr-University Bochum, Bochum, Germany, in 2001.

Dr Jin is a Professor and the Chair in Computational Intelligence with the Department of Computing, University of Surrey, Guildford, U.K., where he heads the Nature Inspired Computing and Engineering Group. His science-driven research interests lie in interdisciplinary areas that bridge the gap between computational intelligence, computational neuroscience, and computational systems biology. He is also particularly interested in nature-inspired, real-world driven problem-solving, such as aerodynamic optimisation, natural gas terminal design, intelligent heating systems, and process optimisation and control. Recently, he has also been carrying out research in feature extraction and construction in images.

Dr Jin has (co)edited five books and three conference proceedings, authored a monograph, and (co)authored over 150 peer-reviewed journal and conference papers. He has been granted eight US, EU and Japan patents. His current research is funded by EC FP7, UK EPSRC and industries, including Airbus, Bosch UK, HR Wallingford and Honda. He has delivered 16 invited keynote speeches at international conferences.

He is an Associate Editor/Editorial Board Member of IEEE Transactions on Cybernetics, IEEE Transactions on NanoScience, and IEEE Computational Intelligence Magazine, Evolutionary Computation (MIT), BioSystems (Elsevier) and Soft Computing (Springer). He is a past Associate Editor of IEEE Transactions on Neural Networks, IEEE Transactions on Systems man and Cybernetics, Part C, and IEEE Transactions on Control Systems Technology.

Dr Jin is currently an IEEE Distinguished Lecturer, Vice President for Technical Activities and an AdCom Member of the IEEE Computational Intelligence Society. He was the recipient of the Best Paper Award of the 2010 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology. He is a Fellow of BCS and Senior Member of IEEE.

Mengjie Zhang is currently Professor of Computer Science at Victoria University of Wellington, where he heads the interdisciplinary Evolutionary Computation Research Group. He is a member of the University Academic Board, a member of the University Postgraduate Scholarships Committee, a member of the Faculty of Graduate Research Board at the University, Associate Dean (Research and Innovation) for Faculty of Engineering, and Chair of the Research Committee of the Faculty and School of Engineering and Computer Science. His research is mainly focused on evolutionary computation, particularly genetic programming, particle swarm optimization, multi-objective optimization and learning classifier systems with application areas of classification with unbalanced data, feature selection and dimensionality reduction, computer vision and image processing, job shop scheduling, and bioinformatics. He is also interested in data mining, machine learning, and web information extraction. Prof Zhang has published over 300 academic papers in refereed international journals and conferences in these areas. He has been serving as an associated editor or editorial board member for five international journals including IEEE Transactions on Evolutionary Computation, the Evolutionary Computation Journal (MIT Press) and Genetic Programming and Evolvable Machines (Springer), and as a reviewer of over 20 international journals. He has been a general/program/technical chair for eight international conferences. He has also been serving as a steering committee member and a program committee member for over 100 international conferences including all major conferences in evolutionary computation. Since 2007, he has been listed as one of the top ten world genetic programming researchers by the GP bibliography (

Prof Zhang is a senior member of IEEE, Chair of the IEEE CIS Evolutionary Computation Technical Committee, a member of IEEE CIS Intelligent System Applications Technical Committee, a vice-chair of the IEEE CIS Task Force on Evolutionary Computer Vision and Image Processing, and the founding chair of the IEEE Computational Intelligence Chapter in the IEEE New Zealand Central Section.

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