Programme
09:00 registration and coffee
09:45 welcome speech
10:00 keynote by Dan Roth
11:00 paper session
- Veronika Cheplygina, David Tax and Marco Loog – Asymmetry in Point Set Dissimilarities
11:20 coffee break
11:40 paper session
- Jan van Rijn and Joaquin Vanschoren – OpenML: An Open Science Platform for Machine Learning
- Hui Li, Peter van der Putten and Maarten Keijzer – Recommending Products using Preference Based Modeling
- Folgert Karsdorp and Antal Van Den Bosch – Identifying Motifs in Folktales using Topic Models
- Suzanne Aussems, Bas Goris, Vincent Lichtenberg, Nanne van Noord, Rick Smetsers and Menno Van Zaanen – Unsupervised identification of compounds
13:00 lunch
14:00 paper session
- Laurens van der Maaten, Minmin Chen, Stephen Tyree and Kilian Weinberger – Learning by Marginalizing Corrupted Features
- Thijs van Ommen – AIC for Conditional Model Selection
- Jesse Krijthe, Tin Kam Ho and Marco Loog – Improving Cross-Validation Classifier Selection Accuracy through Meta-learning
- Wim Wiegerinck, Willem Burgers and Frank Selten – Supermodels: Dynamically Coupled Imperfect Models
- poster spotlights
15:30 coffee break
15:50 paper session
- George Azzopardi and Nicolai Petkov – COSFIRE: A trainable features approach to pattern recognition
- Shengfa Miao, Ugo Vespier, Joaquin Vanschoren, Arno Knobbe and Ricardo Cachucho – Modeling Sensor Dependencies between Multiple Sensor Types
- Nanne van Noord and Eric Postma – Colour-texture analysis using ICA filter banks
- poster spotlights
17:00 poster session and drinks
19:00 dinner
List of posters
1. Michiel Stock, Willem Waegeman and Bernard De Baets:
Learning Relations: Pitfalls and Applications
2. Tom Claassen and Tom Heskes:
A Bayesian Approach to Constraint Based Causal Inference
3. Benoît Frénay, Gauthier Doquire and Michel Verleysen:
Mutual Information: an Adequate Tool for Feature Selection
4. Thomas Fannes, Elien Vandermarliere, Leander Schietgat, Lennart Martens and Jan Ramon:
Predicting trypsin cleavage sites based on sequence information using decision tree ensembles
5. Alberto Baggio, Ugo Vespier and Arno Knobbe:
Data-Adaptive Approximation Selection for Large Time-Series Visualization
6. Rob Konijn and Arno Knobbe:
Detecting Excessive Claim Behavior in Medical Insurance Claims
7. Golnoosh Farnadi, Susana Zoghbi, Marie-Francine Moens and Martine De Cock:
How well do your Facebook status updates express your personality?
8. Umut Güçlü and Marcel van Gerven:
Unsupervised Learning of Features for Bayesian Decoding in Functional Magnetic Resonance Imaging
9. Wouter Duivesteijn and Arno Knobbe:
Exceptional Model Mining — Describing Deviations in Datasets
10. Evgeni Tsivtsivadze, Eveline Lommen, Roy Montijn and Jos van der Vossen:
Semi-supervised Multi-view Gaussian Processes for Microbial Growth Prediction
11. Zhemin Zhu, Djoerd Hiemstra, Peter Apers and Andreas Wombacher:
Empirical Training For Conditional Random Fields
12. Sicco van Sas and Maarten Marx:
Multi-label text classification using parsimonious language models
13. Hilbert J Kappen, Vicenç Gómez and Manfred Opper:
Multiagent Control as a Graphical Model Inference Problem
14. Vincent Van Asch and Walter Daelemans:
An analytical approach to similarity measure selection for selftraining
15. Palupi Kusuma, Dejan Radosavljevik, Frank Takes and Peter van der Putten:
Combining Customer Attribute and Social Network Mining for Prepaid Mobile Churn Prediction
16. Sicco Verwer, Qing Chuan Ye and Yingqian Zhang:
White-box optimization from historical data
17. Daniel Kuehlwein, Jasmin Christian Blanchette, Josef Urban and Cezary Kaliszyk:
MaSh: Machine Learning for Sledgehammer
18. Sultan Imangaliyev, Evgeni Tsivtsivadze, Wim Crielaard and Bart Keijser:
Efficient Feature Selection via Online Co-regularized Algorithm
19. Shengfa Miao and Arno Knobbe:
Traffic Events Identication with a Sensor Network on a Dutch Highway Bridge
20. Antoine Adam and Hendrik Blockeel:
A query language for constraint-based clustering
21. Peter Bloem:
Compression-based inference on graph data