Current Trends in Artificial Intelligence
Although the course is scheduled for both semesters it will only start in the second semester. The lessons take place Fridays from 13:15 till 15:30 o'clock. in IRIDIA:
- The student is able to participatie actively in a scientific debate.
- Student receives an overview of a variety of topics in artificial intelligence
This course is given together with the IRIDIA Lab at the ULB. Different (international) guest lecturers with an expertise in AI will give a talk about their current work in AI.
Examples from the previous years are: The New Science of Networks, Evolutionary Robotics, Neurorobotics, Complex Systems, Bio-Inspiration and Morphogenetic Engineering, Supervised Pattern Set Mining, Data-driven approaches to natural language processing, Computational models of the evolution of speech and language, Big data Bioinformatics.
- Attendance in the lectures is obliged (friday afternoon). Each absence needs to be e-mailed beforehand.
- 60% of the grades come from a programming assignment about one of the lectures.
- The other 40% come from an oral exam about the lectures.
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15/02 Remi Van Trijp (Sony Labs Paris)
- topic: language evolution
- materials: slides // video part 1 // video part 2
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22/2 Tias Guns (K.U.Leuven)
- topic: the intersection between constraint solving and machine learning/data mining
- materials: slides // video part 1 // video part 2
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1/3 Tom De Smedt (Universiteit Antwerpen)
- topic: computers & creativity
- materials: slides // book on 'modelling creativity' // video part 1 // video part 2
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8/3 Vito Trianni (ULB IRIDIA)
- topic: evolutionary robotics
- materials: slides // video part 1 // video part 2
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15/3 Hugues Bersini (ULB IRIDIA)
- topic: The science of complex networks
- materials: slides // video part 1 // video part 2
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22/3 Marco Saerens (UCL)
- topic: Hidden Markov Models: A Short introduction
- materials: slides // video part 1 // video part 2
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29/3 Alain Coletta and David Weiss
- topic: Big data and bio-informatics
- materials: video
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19/4 Dimitri Dejonghe & Renaud Gillon (ONSemi)
- topic: Application of Machine Learning techniques in System-level Design
- materials: slides part 1, part 2 , part 3, // video part 1, part 2
- 26/4 Marie-Francine Moens
- 3/5 Hugues Bersini