Home | Important Dates | Program Committee | Accepted Papers | Program | Author Instructions | Contact | Registration | Accommodation | ML4NLP workshop


ACCEPTED PAPERS

Michaël Rademaker, Bernard De Baets and Hans De Meyer. Improved monotone relabeling of partially non-monotone data.
Yvan Saeys and Yves Van de Peer. Distribution based algorithms for feature weighting, ranking, and selection .
Martijn Kagie, Michiel van Wezel and Patrick J.F. Groenen. A Graphical Shopping Interface Based on Product Attributes.
Tudor Toma, Ameen Abu-Hanna and Robert-Jan Bosman. Temporal Patterns: discovery and use in predictive models. Case study in the Intensive Care.
Stijn Prompers, Matthijs Mulder and Marten Den Uyl. Alternative representations for web page classification.
Linda Peelen, Niels Peek, Nicolette F de Keizer and Robert Jan Bosman. Stratified analysis of multivariate state changes in critically ill patients.
Joaquin Vanschoren, Anneleen Van Assche, Celine Vens and Hendrik Blockeel. Meta-learning from Experiment Databases: An Illustration.
Goele Hollanders, Geert Jan Bex, Marc Gyssens, Ronald Westra and Karl Tuyls. Learning Sparse Networks From Poor Data.
Sicco Verwer, Mathijs de Weerdt and Cees Witteveen. An algorithm for learning real-time automata.
Sander Canisius and Caroline Sporleder. Learning to Segment and Label Semi-Structured Documents with Little or No Supervision.
Leander Schietgat, Jan Ramon and Maurice Bruynooghe. A Polynomial-time Metric for Outerplanar Graphs.
Siegfried Nijssen and Elisa Fromont. Learning Optimal Decision Trees.
Antal van den Bosch and Ko van der Sloot. Superlinear parallelisation of the k-nearest neighbor classifier.
Wojtek Kowalczyk and Dhiraj Hegde. Predicting Web User Behavior with Mixture Models.
Evgueni Smirnov, Mark Winands, Pieter Spronck and Maarten Schadd. Constructing Reliable Classifiers for Road Side Assistance.
Jan Ramon, Snezhana Dubrovskaya and Hendrik Blockeel. Learning Resistance Mutation Pathways of HIV.
Hoskuldur Hlynsson and Maarten van Someren. Transfer Learning Using MDL and a Decision Tree Application.