Learning and Intelligent OptimizatioN
Jan 17-21, 2011, Rome, Italy
Scope of the conference
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 1, LION 2, LION 3 and LION 4 for the previous editions), is aimed at 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.
Best Paper AwardsWe are proud to announce the two best papers of this year's edition. Both prizes have been awarded during the Social Dinner on Thursday.
First prize - Multivariate Statistical Tests for Comparing Classification Algorithms, by Olcay Yildiz, Ozlem Aslan and Ethem Alpaydin.
Second prize - Sequential Model-Based Optimization for General Algorithm Configuration, by Frank Hutter, Holger Hoos and Kevin Leyton-Brown.
Sponsors, proceedings and special issue(sponsorship for LION5 are being renewed now). Technical Co-Sponsorship: Microsoft Research, Associazione Italiana per l'Intelligenza Artificiale, IEEE Computational Intelligence Society
OrganizationConference General Chair: Xin Yao , The University of Birmingham (UK)
Local Organization Co-Chairs: Marco Schaerf and Laura Palagi, Sapienza Università di Roma (Italy)
Technical Program Committee Chair: Carlos Artemio Coello Coello CINVESTAV-IPN (Mexico)
Steering Committee: Roberto Battiti (head), Holger Hoos, Mauro Brunato, Thomas Stuetzle, Christian Blum, Martin Charles Golumbic, Xin Yao, Benjamin W. Wah
Scientific liaison with Springer Verlag Thomas Stuetzle.
Web Chair: Franco Mascia, University of Trento (Italy)
Administration and support to the local organization by: Reactive Search SrL
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LION 5, Learning and Intelligent OptimizatioN, Rome - Italy, Jan 17-21 2011
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