Proceedings

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