LION 11, Eleventh Learning and Intelligent Optimization Conference
Submission deadline: December 18, 2016
Conference dates: 19-21 June, 2017
Conference location: Nizhny Novgorod, Russia
More info: http://intelligent-optimization.org/lion11/
===== Scope =====
Practitioners using heuristic algorithms for hard optimization problems are confronted with the burden of selecting the most appropriate method, in many cases through expensive algorithm configuration and parameter tuning. Scientists seek theoretical insights and demand a sound experimental methodology for evaluating algorithms and assessing strengths and weaknesses. This effort requires a clear separation between the algorithm and the experimenter, who, in too many cases, is "in the loop" as a motivated intelligent learning component. LION deals with 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 online or offline can improve the algorithm design process and simplify the applications of high-performance optimization methods. Combinations of different algorithms can further improve the robustness and performance of the individual components.
This meeting, which continues the successful LION series, explores the intersections and uncharted territories between machine learning, artificial intelligence, mathematical programming and algorithms for hard optimization problems. Russia has a long tradition in optimization theory, computational mathematics and "intelligent learning techniques" (in particular cybernetics and statistics). The location of LION11 in Nizhny is an occasion to meet researchers and consolidate research and human links. In internet time the value of a conference must go well beyond presenting scientific papers. In particular, we are discussing and planning:
- Contests in continuous and discrete optimization.
- Sessions dedicated to commercial software and open source initiatives.
- Parallel computing, supercomputing, and cloud for "big optimization".
- Elevator pitches about new and crazy ideas (also by PhD students).
- Tutorials about methods and software.
===== Submission Instructions =====
Please prepare your paper in English using the Lecture Notes in Computer Science (LNCS) template. Papers must be submitted in PDF.
Types of Submissions
When submitting a paper to LION11, authors are required to select one of the following three types of papers:
* Long paper: original novel and unpublished work (max. 15 pages in LNCS format);
* Short paper: an extended abstract of novel work (max. 6 pages in LNCS format);
* Work for oral presentation only (no page restriction; any format). For example, work already published elsewhere, which is relevant and which may solicit fruitful discussion at the conference.
===== Publication Details =====
Post-conference proceedings are published by Springer-Verlag in its LNCS series. A special issue of a scientific journal with invited extended version of the best papers is being planned.
===== Further Information =====
Up-to-date information will be published on the web site
http://intelligent-optimization.org/lion11/. For information
about local arrangements, registration forms, etc., please refer to the
above-mentioned web site or contact the local organizers.
LION 11 will be collocated with the 7th International Conference on Network Analysis (June 22-24, 2017).
===== Important Dates =====
Submission deadline December 18, 2016
Notification of acceptance March 10, 2017
Conference June 19-21, 2017
===== LION 11 Committee =====
General Chair
Yaroslav Sergeyev, University of Calabria (Italy) and Lobachevsky University, Nizhny (Russia).
Local organization committee
Roman Strongin (Chair), Victor Kasantsev (Vice-Chair), Victor Gergel (Vice-Chair), Vladimir Grishagin, Dmitri Balandin, Konstantin Barkalov, Dmitri Kvasov.
Steering committee
Roberto Battiti (head), Holger Hoos, Youssef Hamadi, Mauro Brunato, Thomas Stuetzle, Christian Blum, Martin Charles Golumbic, Marc Schoenauer, Xin Yao, Benjamin W. Wah.
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