| Thursday, May 11 |
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| 08.30h | Registration |
| 09.15h | Opening (Organizing committee) |
| 09.30h | Invited Talk: Bernhard Schölkopf (Max Planck Institute for Biological Cybernetics)
Recent advances in kernel methods |
| 10.30h | Coffee Break |
| 11.00h | Machine learning: methodology |
| | Pierre Geurts, Raphael Maree and Louis Wehenkel
Segment and combine: a generic approach for supervised learning of invariant
classifiers from topologically structured data |
| | Anneleen Van Assche and Hendrik Blockeel
Simulating bagging without bootstrapping |
| | Stijn Vanderlooy, Ida Sprinkhuizen-Kuyper and Evgeni Smirnov
Reliable classifiers in ROC space |
| 12.30h | Lunch Break |
| 14.00h | Time series analysis |
| | Sicco Verwer, Mathijs de Weerdt and Cees Witteveen
Identifying an automaton model for timed data |
| | Elena Tsiporkova and Veselka Boeva
Dynamic time warping techniques for missing value estimation in gene expression time series |
| 15.00h | Evolutionary algorithms |
| | Lars Zwanepol Klinkmeijer, Edwin de Jong and Marco Wiering
A serial population genetic algorithm for dynamic optimization problems |
| 15.30h | Coffee Break |
| 16.00h | Machine learning: Theory |
| | Jan Poland and Marcus Hutter
Universal learning of repeated matrix games |
| | Joaquin Vanschoren and Hendrik Blockeel
Towards understanding learning behavior |
| | Shane Legg and Marcus Hutter
A formal measure of machine intelligence |
| 19.00h | Little walk in the historical part of Ghent |
| 20.00h | Social dinner |
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| Friday, May 12 |
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| 09.00h | Registration |
| 09.30h | Invited Talk: Eyke Hüllermeier (Otto-von-Guericke-Universität Magdeburg)
Learning by Pairwise Comparison: Classification, Ranking, and Related Problems |
| 10.30h | Coffee Break |
| 11.00h | Text, music and language mining |
| | Jornt de Gruijl and Marco Wiering
Musical instrument classification using democratic liquid state machines |
| | Caroline Sporleder, Marieke van Erp, Tijn Porcelijn and Antal van den Bosch
Correcting wrong-column errors in text databases |
| | Veronique Hoste and Walter Daelemans
Comparing learning approaches to language learning. There is more to it than bias. |
| 12.30h | Lunch Break |
| 14.00h | Machine learning in Bioinformatics and Biomedicine |
| | Yvan Saeys and Yves Van de Peer
Enhancing coding potential prediction for short sequences using complementary sequence features and feature selection |
| | Sophia Katrenko and Pieter Adriaans
Learning biomedical relations via dependency tree levels |
| | Fabian Guiza, Daan Fierens, Jan Ramon, Hendrik Blockeel, Geert Meyfroid, Maurice Bruynooghe and Greet Van Den Berghe
Predictive data mining in intensive care |
| 15.30h | Coffee Break |
| 16.00h | Reinforcement learning / Data preparation |
| | Damien Ernst, Guy-Bart Stan, Jorge Goncalves and Louis Wehenkel
Clinical data based optimal STI strategies for HIV; a reinforcement learning approach |
| | Pieter Adriaans
Speed search in truth tables (SSTT) A complete inductive approach to SAT |
| | Michael Rademaker, Bernard De Baets and Hans De Meyer
Data sets for supervised ranking: to clean or not to clean |
| 18.00h - ... | Belgian beer tasting event |
