LION 14: 14th Learning and Intelligent OptimizatioN Conference Hotel Cabo Verde Athens, Greece, May 24-28, 2020 |
Conference website | http://www.caopt.com/LION14/index.php |
Submission link | https://easychair.org/conferences/?conf=lion14 |
14th Learning and Intelligent OptimizatioN Conference, May 24-28, 2020, Athens, Greece
Website: http://www.caopt.com/LION14/
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, 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.
Submission Guidelines
All papers must be original and not simultaneously submitted to another journal or conference. The following paper categories are welcome:
- Long paper: original novel and unpublished work (max. 15 pages in LNCS format);
- Short paper: an extended abstract of novel work (max. 4 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.
Committees
Program Committee
- Roberto Battiti, Università degli Studi di Trento, Director of the LION lab (machine Learning and Intelligent OptimizatioN)
Organizing committee
- Panos Pardalos, Center for Applied Optimization, University of Florida (USA) - General Chair
- Mauro Brunato, Università degli Studi di Trento, machine Learning and Intelligent OptimizatioN (LION) research (Italy) - General Chair
- Ilias Kotsireas , CARGO Lab, Wilfrid Laurier University (Canada) - Local Chair
Contact
All questions about submissions should be emailed to roberto.battiti@unitn.ot