Start
End
Schedule
V Monday 19 May
V Morning
08:00
* Registration desk open
09:15 09:30
* Welcome
09:30 10:30
V Invited talk (Chair: Damien Ernst)
* Susan Murphy. Machine learning and reinforcement learning in clinical research
10:30 11:00
* Coffee break
11:00 12:30
V session 1
V Session 1.1: Reinforcement learning, planning, and games (Chair: Susan Murphy)
11:00 11:20
* Tom Croonenborghs, Kurt Driessens and Maurice Bruynooghe. Learning a transfer function for reinforcement learning problem
11:20 11:40
* Boris Defourny, Damien Ernst and Louis Wehenkel. Perturb and combine in sequential decision making under uncertainty
11:40 12:00
* Raphael Fonteneau, Louis Wehenkel and Damien Ernst. Variable selection for dynamic treatment regimes: a reinforcement learning approach
12:00 12:20
* Jan Lemeire. An alternative approach for playing complex games like chess
V Session 1.2: Graphical and relational models (Chair: Kristel Van Steen)
11:00 11:20
* Luc De Raedt. ProbLog and its applications to link mining
11:20 11:40
* Bernd Gutmann, Angelika Kimmig, Luc De Raedt and Kristian Kersting. Parameter learning in probabilistic databases: a least squares approach
11:40 12:00
* Ingo Thon, Niels Landwehr and Luc De Raedt. CPT-L: an efficient model for relational stochastic processes
12:00 12:20
* Vincent Auvray and Louis Wehenkel. Learning inclusion-optimal chordal graphs
12:20 12:40
* Sourour Ammar, Philippe Leray, Boris Defourny and Louis Wehenkel. Density estimation with ensembles of randomized poly-trees
V Afternoon
14:00 15:00
V Invited talk (Chair: Raphaël Marée)
* Bill triggs. Scene segmentation with latent topic markov field models - and - classification and dimensionality reduction using convex class models
15:00 15:30
* Coffee break
15:30 17:30
V Session 2
V Session 2.1: Vision and speech (Chair: Bill Triggs)
15:30 15:50
* Fabien Scalzo, Georgios Bebis, Mircea Nicolescu and Leandro Loss. Evolutionary learning of feature fusion hierarchies
15:50 16:10
* Cedric Simon, Jerome Meessen and Christophe De Vleeschouwer. Using decision trees to build an event recognition framework for automated visual surveillance
16:30 16:50
* Raphaël Marée, Pierre Geurts and Louis Wehenkel. Content-based image retrieval by indexing random subwindows with randomized trees
16:50 17:10
* Herman Stehouwer. IGForest: from tree to forest
17:10 17:30
* Marie Dumont, Raphaël Marée, Pierre Geurts and Louis Wehenkel. Fast image annotation with random subwindows and multiple output randomized trees
17:10 17:30
* Thomas Drugman. On the use of machine learning in statistical parametric speech synthesis
V Session 2.1: Feature selection and active learning (Chair: Yvan Saeys)
15:30 15:50
* Yvan Saeys, Thomas Abeel and Yves Van de Peer. Towards robust feature selection techniques
15:50 16:10
* Marieke van Erp, Antal van den Bosch, Piroska Lendvai and Steve Hunt. Feature selection techniques for database cleansing: knowledge-driven vs. greedy search
16:10 16:30
* Van Anh Huynh-Thu, Louis Wehenkel and Pierre Geurts. Deriving p-values for tree-based variable importance measures
16:30 16:50
* Robby Goetschalckx, Scott Sanner and Kurt Driessens. Linear regression using costly features
16:50 17:10
* Dirk Gorissen, Tom Dhaene and Eric Laermans. Automatic regression modeling with active learning
17:10 17:30
* Kurt De Grave, Jan Ramon and Luc De Raedt. Active learning for primary drug screening
* Conference dinner
V Tuesday 20 May
V Morning
09:30 10:30
V Invited talk (Chair: Pierre Geurts)
* Johannes Fürnkranz. Preference learning
10:30 11:00
* Coffee break
11:00 12:40
V Session 3
V Session 3.1: Ranking, complex outputs, and trees (Chair: Johannes Fürnkranz)
11:00 11:20
* Willem Waegeman, Bernard De Baets and Luc Boullart. When can we simplify a one-versus-one multi-class classifier to a single ranking?
11:20 11:40
* Michael Rademaker, Bernard De Baets and Hans De Meyer. Monotone relabeling of partially non-monotone data: restoring regular or stochastic monotonicity
11:40 12:00
* Pierre Geurts, Louis Wehenkel and Florence d'Alché-Buc. Learning in kernelized output spaces with tree-based methods
12:00 12:20
* Beau Piccart, Jan Struyf and Hendrik Blockeel. Selective inductive transfer
12:20 12:40
* Justus Piater, Fabien Scalzo and Renaud Detry. Vision as inference in a hierarchical markov network
V Session 3.2: Semi-supervised learning, missing data, and automata (Chair: Pierre Dupont)
11:00 11:20
* Jerôme Callut, Kevin Françoisse, Marco Saerens and Pierre Dupont. Semi-supervised classification in graphs using bounded random walks
11:20 11:40
* Amin Mantrach, Marco Saerens and Luh Yen. The sum-over-paths covariance: a novel covariance measure
11:40 12:00
* Jort Gemmeke. Classification on incomplete data using sparse representations: imputation is optional
12:00 12:20
* Yann-Michaël De Hauwere, Peter Vrancx and Ann Nowé. Multi-agent state space aggregation using generalized learning automata
12:20 12:40
* Sicco Verwer, Mathijs de Weerdt and Cees Witteveen. Efficiently learning timed models from observations
V Afternoon
14:00 15:00
V Invited talk (Chair: Louis Wehenkel)
* Gunnar Rätsch. Boosting, margins, and beyond
15:00 15:30
* Coffee break
15:30 17:30
V Session 4
V Session 4.1: Bioinformatics (Chair: Gunnar Rätsch)
15:30 15:50
* Thomas Abeel, Yvan Saeys and Yves Van de Peer. ProSOM: Core promoter identification in the human genome
15:50 16:10
* Sofie Van Landeghem, Yvan Saeys, Bernard De Baets and Yves Van de Peer. Benchmarking machine learning techniques for the extraction of protein-protein interactions from text
16:10 16:30
* Aalt-Jan van Dijk, Dirk Bosch, Cajo ter Braak, Sander van der Krol, and Roeland van Ham. Predicting sub-Golgi localization of glycosyltransferases
16:30 16:50
* Vincent Botta, Pierre Geurts, Sarah Hansoul and Louis Wehenkel. Prediction of genetic risk of complex diseases by supervised learning
16:50 17:10
* Gilles Meyer and Rodolphe Sepulchre. Component analysis for genome-wide association studies
17:10 17:30
* Fabien Scalzo, Peng Xu, Marvin Bergsneider and Xiao Hu. Morphological feature extraction of intracranial pressure signals via nonlinear regression
V Session 4.2: Applications (Chair: Bernard Manderick)
15:30 15:50
* Tim Van de Cruys. An extended NMF algorithm for word sense discrimination
15:50 16:10
* Koen Smets, Bart Goethals and Brigitte Verdonk. Automatic vandalism detection in wikipedia: towards a machine learning approach
16:10 16:30
* Bertrand Cornelusse, Louis Wehenkel and Gerald Vignal. Supervised learning of short-term strategies for generation planning
16:30 16:50
* Jean-Michel Dricot, Mathieu Van der Haegen, Yann-Ael Le Borgne and Gianluca Bontempi. Performance Evaluation of machine learning techniques for the localization of users in wireless sensor networks
16:50 17:10
* Marc Ponsen, Jan Ramon, Kurt Driessens, Tom Croonenborghs and Karl Tuyls. Bayes-relational learning of opponent models from incomplete information in no-limit poker
17:10 17:30
* Francis wyffels, Benjamin Schrauwen and Dirk Stroobandt. System modeling with Reservoir Computing
17:30 17:45
* Closing