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EVOLUTIONARY-COMPUTING  April 2014

EVOLUTIONARY-COMPUTING April 2014

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Subject:

[LION 2015] Call for papers LION'9, January 12-16 2015, Lille (France)

From:

Marie-Eléonore Marmion <[log in to unmask]>

Reply-To:

Marie-Eléonore Marmion <[log in to unmask]>

Date:

Fri, 18 Apr 2014 15:19:30 +0200

Content-Type:

text/plain

Parts/Attachments:

Parts/Attachments

text/plain (85 lines)

[Apologies for multiple copies]

================================================
CALL FOR PAPERS

Learning and Intelligent OptimizatioN Conference
LION9 , Lille, FRANCE, Jan. 12-16, 2015.
http://www.lifl.fr/LION9/

================================================
Learning and Intelligent OptimizatioN Conference LION9


CALL FOR SESSIONS AND PAPERS

The large variety of heuristic algorithms for hard optimization problems 
raises numerous interesting and challenging issues. Practitioners are 
confronted with the burden of selecting the most appropriate method, in 
many cases through an expensive algorithm configuration and parameter 
tuning process, and subject to a steep learning curve. Scientists seek 
theoretical insights and demand a sound experimental methodology for 
evaluating algorithms and assessing strengths and weaknesses. A 
necessary prerequisite for this effort is a clear separation between the 
algorithm and the experimenter, who, in too many cases, is "in the loop" 
as a crucial intelligent learning component. Both issues are related to 
designing and engineering ways of "learning" about the performance of 
different techniques, and ways of using past experience about the 
algorithm behavior to improve performance in the future. Intelligent 
learning schemes for mining the knowledge obtained from different runs 
or during a single run can improve the algorithm development and design 
process and simplify the applications of high-performance optimization 
methods. Combinations of algorithms can further improve the robustness 
and performance of the individual components provided that sufficient 
knowledge of the relationship between problem instance characteristics 
and algorithm performance is obtained.

This meeting, which continues the successful series of LION events (see 
LION 5 in Rome, LION 6 in Paris, LION 7 in Catania, and LION 8 in 
Gainesville), is exploring the intersections and uncharted territories 
between machine learning, artificial intelligence, mathematical 
programming and algorithms for hard optimization problems. The main 
purpose of the event is to bring together experts from these areas to 
discuss new ideas and methods, challenges and opportunities in various 
application areas, general trends and specific developments.

Already confirmed invited speakers are: David Corne (Heriot-Watt 
University, UK), Alex Freitas (University of Kent, UK), Daniel Le Berre 
(University of Lens, France).

LION will continue to be one of the most respected conferences for 
researchers working on Learning and Optimization by ensuring a strict 
selection of paper with an average selection rate lower than 40%.

Following the tradition of LION, the proceedings will be published after 
the conference in the Series Lecture Notes in Computer Science (LNCS) by 
Springer.

**Important dates**
Session proposal: June 30th 2014
Paper submission: October 10th 2014
Author Notification: November 25th 2014
Registration: December 17th 2014
Camera ready for pre-proceedings: January 3rd 2015
Conference: January 12-16th 2015

**Contacts**
[log in to unmask]

**Committees**
General Chairs:
- Clarisse Dhaenens, University of Lille 1, France
- Laetitia Jourdan, University of Lille 1, France
- Marie-Eléonore Marmion, University of Lille 1, France

Steering Committee:
- Roberto Battiti (head), University of Trento, Italy
- Holger Hoos, University of British Columbia, Canada
- Youssef Hamadi, Microsoft Research Center, UK
- Mauro Brunato, University of Trento, Italy
- Thomas Stuetzle, Free University of Brussels, Belgium
- Christian Blum, University of the Basque Country, Spain
- Martin Charles Golumbic, University of Haifa, Israel
- Marc Schoenauer, INRIA, France
- Xin Yao, University of Birmingham , UK
- Benjamin W. Wah, University of Illinois, USA

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