CEC Deadline extension

Important Dates

Paper submission deadline: December 19, 2014 January 16, 2015 (Extended)

Paper acceptance notification: February 20, 2015

Final paper submission deadline: March 13, 2015

Conference dates: May 25-28, 2015

Special Session on

New Directions in Evolutionary Machine Learning

Motivation

Evolutionary Machine Learning (EML) explores technologies that integrate machine learning with evolutionary computation for tasks including optimization, classification, regression, and clustering. Since machine learning contributes to a local search while evolutionary computation contributes to a global search, one of the fundamental interests in EML is a management of interactions between learning and evolution to produce a system performance that cannot be achieved by either of these approaches alone. Historically, this research area was called GBML (genetics-based machine learning) and it was concerned with learning classifier systems (LCS) with its numerous implementations such as fuzzy learning classifier systems (Fuzzy LCS). More recently, EML has emerged as a more general field than GBML; EML covers a wider range of machine learning adapted methods such as genetic programming for ML, evolving ensembles, evolving neural networks, and genetic fuzzy systems; in short, any combination of evolution and machine learning. EML is consequently a broader, more flexible and more capable paradigm than GBML. From this viewpoint, the aim of this special session is to explore potential EML technologies and clarify new directions for EML to show its prospects. For this purpose, this special session focuses on, but is not limited to, the following areas in EML:

– Evolutionary learning systems (e.g., learning classifier systems) – Evolutionary fuzzy systems

– Evolutionary data mining - Evolutionary reinforcement learning - Evolutionary neural networks

– Evolutionary adaptive systems       – Artificial immune systems - Accuracy-Interpretability tradeoff in EML

– Applications and theory of EML – Genetic programming applied to machine learning

– Evolutionary feature selection and construction for machine learning - Transfer learning; learning blocks of knowledge (memes, code, etc.) and evolving the sharing to related problem domains

Important Dates

Paper submission deadline: December 19, 2014 January 16, 2015 (Extended)

Paper acceptance notification: February 20, 2015

Final paper submission deadline: March 13, 2015

Conference dates: May 25-28, 2015

Paper Submission

Special session papers are treated the same as regular papers and must be submitted via the CEC 2015 submission website. To submit your paper to this special session, you have to choose our special session (ID SS52) on the submission page.

Organizers

  • Keiki Takadama, The University of Electro-Communications, Japan (Contact: keiki@inf.uec.ac.jp)
  • Tim Kovacs, University of Bristol, UK.
  • Yusuke Nojima, Osaka Prefecture University, Japan
  • Will Browne, Victoria University of Wellington, New Zealand
  • Masaya, Nakata, The University of Electro-Communications, Japan

 

Special Session URL: https://sites.google.com/site/cec2015sseml/

Conference URL: http://sites.ieee.org/cec2015/

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Call for Papers

Evolutionary Computation, Volume 22, Issue 4, Page 710-710, Winter 2014.

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New Directions in Evolutionary Machine Learning at 2015 IEEE Congress on Evolutionary Computation (CEC 2015)

Call to submit a paper for the special session on New Directions in Evolutionary Machine Learning at 2015 IEEE Congress on Evolutionary Computation (CEC 2015) which will be held in Sendai, Japan at May 25-28, 2015.
If you are interested in our special session and planing to submit a paper, please let us know beforehand. We would like to have a list of tentative papers. Of course, you can submit it without the reply to this message. Please choose the session ID SS52 on the submission system.

Special Session: New Directions in Evolutionary Machine Learning
Organizers: Keiki Takadama, Tim Kovacs, Yusuke Nojima, Will Browne, Masaya Nakata

Evolutionary Machine Learning (EML) explores technologies that integrate machine learning with evolutionary computation for tasks including optimization, classification, regression, and clustering. Since machine learning contributes to a local search while evolutionary computationcontributes to a global search, one of the fundamental interests in EML is a management of interactions between learning and evolution to produce a system performance that cannot be achieved by either of these approaches alone. Historically, this research area was called GBML (genetics-based machine learning) and it was concerned with learning classifier systems (LCS) with its numerous implementations such as fuzzy learning classifier systems(Fuzzy LCS). More recently, EML has emerged as a more general field than GBML; EML covers a wider range of machine learning adapted methods such as genetic programming for ML, evolving ensembles, evolving neural networks, and genetic fuzzy systems; in short, any combination of evolution and machine learning. EML is consequently a broader, more flexible and more capable paradigm than GBML. From this viewpoint, the aim of this special session is to explore potential EML technologies and clarify new directions for EML to show its prospects. For this purpose, this special session focuses on, but is not limited to, the following areas in EML:

– Evolutionary learning systems (e.g., learning classifier systems)
– Evolutionary fuzzy systems
– Evolutionary data mining
– Evolutionary reinforcement learning
– Evolutionary neural networks
– Evolutionary adaptive systems colleagues,
– Artificial immune systems
– Genetic programming applied to machine learning
– Evolutionary feature selection and construction for machine learning
– Transfer learning; learning blocks of knowledge (memes, code, etc.) and evolving the sharing to related problem domains
– Accuracy-Interpretability tradeoff in EML
– Applications and theory of EML

Important dates are as follows:
– Paper Submission Deadline: December 19, 2014
– Paper Acceptance Notification: February 20, 2015
– Final Paper Submission Deadline: March 13, 2015
– Early Registration: March 13, 2015
– Conference Dates: May 25-28, 2015

Further information about the special session and the conference can be found:
– 2015 IEEE Congress on Evolutionary Computation
http://sites.ieee.org/cec2015/
– Special Session on New Directions in EML
https://sites.google.com/site/cec2015sseml/

Best regards,
Keiki, Tim, Yusuke, Will, and Masaya

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Yusuke NOJIMA, Dr.

Dept. of Computer Science and Intelligent Systems Graduate School of Engineering Osaka Prefecture University

Gakuen-cho 1-1, Naka-ku, Sakai, Osaka 599-8531, JAPAN
Phone: +81-72-254-9198, FAX: +81-72-254-9915
Email: nojima@cs.osakafu-u.ac.jp

http://www.cs.osakafu-u.ac.jp/ci/

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

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IEEE Transactions on Evolutionary Computation information for authors

Provides instructions and guidelines to prospective authors who wish to submit manuscripts.

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IEEE Transactions on Evolutionary Computation information for authors

Provides instructions and guidelines to prospective authors who wish to submit manuscripts.

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IEEE Transactions on Evolutionary Computation information for authors

Provides instructions and guidelines to prospective authors who wish to submit manuscripts.

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IEEE Transactions on Evolutionary Computation information for authors

Provides instructions and guidelines to prospective authors who wish to submit manuscripts.

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IEEE Transactions on Evolutionary Computation information for authors

Provides instructions and guidelines to prospective authors who wish to submit manuscripts.

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IEEE Transactions on Evolutionary Computation information for authors

Provides instructions and guidelines to prospective authors who wish to submit manuscripts.

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IEEE Transactions on Evolutionary Computation information for authors

Provides instructions and guidelines to prospective authors who wish to submit manuscripts.

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