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teaching:mfe:ia [2017/04/20 18:32] stuetzle [Software framework for Ant Colony Optimization] |
teaching:mfe:ia [2018/04/19 17:07] stuetzle [Text Categorisation and quality control through automatic language processing] |
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| - | ====== MFE 2015-2016 : Intelligence Artificielle ====== | + | ====== MFE 2017-2018 : Intelligence Artificielle ====== |
| ===== Introduction ===== | ===== Introduction ===== | ||
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| * Contact : [[http://code.ulb.ac.be/iridia.people.php?id=1|Hugues Bersini (IRIDIA)]] | * Contact : [[http://code.ulb.ac.be/iridia.people.php?id=1|Hugues Bersini (IRIDIA)]] | ||
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| + | ===== Text Categorisation and quality control through automatic language processing ===== | ||
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| + | This thesis is developed in collaboration with the Energy Efficiency in Industrial Processes (EEIP) company. EEIP is a global industry information network. As part of their activities, they disseminate case studies to various network groups. The goal of the project is to develop an automatic language processing algorithm capable to evaluate the quality (accept / reject) of the proposed case studies and to allocate them to single/multiple categories. Testing and training the algorithm is a key part as it not only requires development and testing of concepts such as how to evaluate quality or definition of requirements for multiple category allocation but the project also has | ||
| + | to be developed in a limited data environment (+/- 1000 case studies as training set). | ||
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| + | Required skills: A background in machine learning would be helpful. | ||
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| + | * Contacts : | ||
| + | * [[http://iridia.ulb.ac.be/~stuetzle|Thomas Stützle (IRIDIA)]] | ||
| + | * [[https://www.ee-ip.org/|Jürgen Ritzek (EE-IP)]] | ||
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| * Contacts : | * Contacts : | ||
| * [[http://iridia.ulb.ac.be/~mdorigo|Marco Dorigo (IRIDIA)]] | * [[http://iridia.ulb.ac.be/~mdorigo|Marco Dorigo (IRIDIA)]] | ||
| + | * [[http://iridia.ulb.ac.be/~stuetzle|Thomas Stützle (IRIDIA)]] | ||
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| + | ===== Automated configuration of multi-objective continuous optimizers ===== | ||
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| + | Many problems arising in real-world applications involve the optimization of various, often conflicting objectives. While the design of algorithms for tackling multi-objective problems has usually done manually, over the recent years automated design methodologies have been established and proved to be very powerful. | ||
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| + | The goal of this project is to extend the automated design to multi-objective continuous optimization problems. As the basis of the approach, a framework based on the two-phase plus Pareto local search approach will be developed into which basic search techniques for continuous optimization will be integrated. The goal is to build first a flexible framework from which then in a second step effective multi-objective optimizers will be generated exploiting automated algorithm design techniques. The final goal of this work is to participate in algorithm competitions with the goal of challenging the methodology. | ||
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| + | Required skills: The candidate should have very good analytical as well as programming skills. | ||
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| + | * Contacts : | ||
| * [[http://iridia.ulb.ac.be/~stuetzle|Thomas Stützle (IRIDIA)]] | * [[http://iridia.ulb.ac.be/~stuetzle|Thomas Stützle (IRIDIA)]] | ||