Difference between revisions of "Optimization Group Meetings"
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==Literature Sessions== |
==Literature Sessions== |
Revision as of 10:40, 20 May 2010
Breakfast Meetings
Purpose
Breakfast meetings are informal meetings where there is a general discussion or someone presents their work. And additional goal is to have breakfast together.
Organization
- Send an email to the responsible of Optimization Meetings. Mention your name, your affiliation, the date, time and room, and a short summary of what you are going to talk about.
- Add a new entry to the table below.
- Bring breakfast.
History of Breakfast Meetings
Date | Presenter | Summary |
---|---|---|
2010-05-20 | Marco Montes | The social learning strategies tournament, organized as part of the
cultaptation project, and its results were described. No ideas about algorithm portfolios were discussed. |
2010-05-?? | Renaud Lenne | ??? |
2010-04-29 | Franco Mascia | The maximum clique problem, state of the art and ACO [1] [2] [3] |
2010-03-18 | Sabrina Oliveira | Achieved results from the application of the Population Based Ant Colony Optimisation algorithm to TSP. |
2010-02-11 | Sara Ceschia | An overview of Container Loading Problems. |
2010-01-21 | Yuan, Zhi (Eric) | Rice cooker vs. the idea of tuning. |
2010-01-07 | Thomas Stüztle | General discussion about the optimization group. |
Literature Sessions
Purpose
The goal of the Literature Sessions is to examine and discuss particularly interesting papers from the research literature. For each session, one paper will be selected, there will be a short presentation (10-15 minutes) about the contents, and a discussion will ensue. Sessions will last around 40-45 minutes. Attendants should read the paper before the session in order to have a productive discussion.
Organization
- Book a room (ask Muriel).
- Send an email to the responsible of Optimization Meetings. Mention your name, your affiliation, the date, time and room, a reference to the paper and the URL where it can be obtained. Also, attach the paper in PDF.
- Add a new entry to the table below. Please add a complete bibliographic reference (you may find it in the homepages of the authors) and a hyperlink to a PDF (links to http://dx.doi.org are preferred).
History of Literature Sessions
Date | Presenter | Paper discussed |
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2010-05-07 | Zhi (Eric) Yuan | Hydra: Automatically Configuring Algorithms for Portfolio-Based Selection. L. Xu, H.H. Hoos, K. Leyton-Brown. To appear at the Conference of the Association for the Advancement of Artificial Intelligence (AAAI-10), 2010. [4] |
2010-03-04 | Sara Ceschia | A. Schaerf and L. Di Gaspero. Slides of the tutorial "An Overview of Local Search Software Tools" given at "Learning and Intelligent OptimizatioN (LION 2007)", December 8-12, 2007, Trento, Italy.
L. Di Gaspero and A. Schaerf. EASY LOCAL++: An object-oriented framework for flexible design of local search algorithms. Software — Practice & Experience, 33(8):733–765, July 2003. [5] S. Cahon, N. Melab and T. El Ghazali. ParadisEO: A Framework for the Reusable Design of Parallel and Distributed Metaheuristics. Journal of Heuristics, 10(3):357-380, November 2004. [6] |
2010-02-19 | Sabrina M. de Oliveira | A study on the use of non-parametric tests for analyzing the evolutionary algorithms' behaviour: a case study on the CEC'2005 Session on Real Parameter Optimization. S. Garcia, D. Molina, M. Lozano, F. Herrera - Journal of Heuristics, Volume 15, pp. 617-644, 2009. [7] |
2010-02-04 | Thomas Stüztle | Analyzing Bandit-based Adaptive Operator Selection Mechanisms. Ãlvaro Fialho, Luis Da Costa, Marc Schoenauer and Michéle Sebag. |
2010-01-14 | Jérémie Dubois-Lacoste | SATzilla: Portfolio-based Algorithm Selection for SAT. L. Xu, F. Hutter, H. H. Hoos, K. Leyton-Brown - Journal of Artificial Intelligence Research, Volume 32, pp. 565-606, 2008. [8] |
2009-12-11 | Manuel López-Ibáñez | SATenstein: Automatically Building Local Search SAT Solvers From Components. Ashiqur R. KhudaBukhsh, Lin Xu, Holger H. Hoos and Kevin Leyton-Brown - Proceedings of the 21st International Joint Conference on Artificial Intelligence (IJCAI-09), pp. 517-524, 2009. [9] |