14. ECML 2003: Cavtat-Dubrovnik, Croatia

Invited Papers

• Pieter W. Adriaans:
  From Knowledge-Based to Skill-Based Systems: Sailing as a Machine Learning Challenge. 1-8
  
• Leo Breiman:
  Two-Eyed Algorithms and Problems. 9
  
• Christos Faloutsos:
  Next Generation Data Mining Tools: Power Laws and Self-similarity for Graphs, Streams and Traditional Data. 10-15
  
• Donald B. Rubin:
  Taking Causality Seriously: Propensity Score Methodology Applied to Estimate the Effects of Marketing Interventions. 16-22
  

Contributed Papers

• Ulf Brefeld, Peter Geibel, Fritz Wysotzki:
  Support Vector Machines with Example Dependent Costs. 23-34
  
• Pedro Campos, Thibault Langlois:
  Abalearn: A Risk-Sensitive Approach to Self-play Learning in Abalone. 35-46
  
• Chien Chin Chen, Yao-Tsung Chen, Yeali S. Sun, Meng Chang Chen:
  Life Cycle Modeling of News Events Using Aging Theory. 47-59
  
• François Coste, Daniel Fredouille:
  Unambiguous Automata Inference by Means of State-Merging Methods. 60-71
  
• Paul A. Crook, Gillian Hayes:
  Could Active Perception Aid Navigation of Partially Observable Grid Worlds? 72-83
  
• Walter Daelemans, Véronique Hoste, Fien De Meulder, Bart Naudts:
  Combined Optimization of Feature Selection and Algorithm Parameters in Machine Learning of Language. 84-95
  
• Damien Ernst, Pierre Geurts, Louis Wehenkel:
  Iteratively Extending Time Horizon Reinforcement Learning. 96-107
  
• César Ferri, José Hernández-Orallo, Miguel A. Salido:
  Volume under the ROC Surface for Multi-class Problems. 108-120
  
• César Ferri, Peter A. Flach, José Hernández-Orallo:
  Improving the AUC of Probabilistic Estimation Trees. 121-132
  
• Jörg Fischer, Kristian Kersting:
  Scaled CGEM: A Fast Accelerated EM. 133-144
  
• Johannes Fürnkranz, Eyke Hüllermeier:
  Pairwise Preference Learning and Ranking. 145-156
  
• Pascal Garcia:
  A New Way to Introduce Knowledge into Reinforcement Learning. 157-168
  
• Amaury Habrard, Marc Bernard, Marc Sebban:
  Improvement of the State Merging Rule on Noisy Data in Probabilistic Grammatical Inference. 169-180
  
• Pieter Jan't Hoen, Sander M. Bohte:
  COllective INtelligence with Sequences of Actions - Coordinating Actions in Multi-agent Systems. 181-192
  
• Matti Kääriäinen, Tapio Elomaa:
  Rademacher Penalization over Decision Tree Prunings. 193-204
  
• David Kauchak, Charles Elkan:
  Learning Rules to Improve a Machine Translation System. 205-216
  
• Rinat Khoussainov, Nicholas Kushmerick:
  Optimising Performance of Competing Search Engines in Heterogeneous Web Environments. 217-228
  
• Frédéric Koriche, Joël Quinqueton:
  Robust k-DNF Learning via Inductive Belief Merging. 229-240
  
• Niels Landwehr, Mark Hall, Eibe Frank:
  Logistic Model Trees. 241-252
  
• Jianguo Lee, Jingdong Wang, Changshui Zhang:
  Color Image Segmentation: Kernel Do the Feature Space. 253-264
  
• Marie-Jeanne Lesot, Florence d'Alché-Buc, George Siolas:
  Evaluation of Topographic Clustering and Its Kernelization. 265-276
  
• Yan Liu, Jaime G. Carbonell, Rong Jin:
  A New Pairwise Ensemble Approach for Text Classification. 277-288
  
• Koichi Moriyama, Masayuki Numao:
  Self-evaluated Learning Agent in Multiple State Games. 289-300
  
• ShyamSundar Rajaram, Ashutosh Garg, Xiang Sean Zhou, Thomas S. Huang:
  Classification Approach towards Banking and Sorting Problems. 301-312
  
• Bohdana Ratitch, Doina Precup:
  Using MDP Characteristics to Guide Exploration in Reinforcement Learning. 313-324
  
• Marko Robnik-Sikonja:
  Experiments with Cost-Sensitive Feature Evaluation. 325-336
  
• Roberto Santana:
  A Markov Network Based Factorized Distribution Algorithm for Optimization. 337-348
  
• Marc Sebban, Henri-Maxime Suchier:
  On Boosting Improvement: Error Reduction and Convergence Speed-Up. 349-360
  
• James G. Shanahan, Norbert Roma:
  Improving SVM Text Classification Performance through Threshold Adjustment. 361-372
  
• Khalil Sima'an, Luciano Buratto:
  Backoff Parameter Estimation for the DOP Model. 373-384
  
• Dorian Suc, Ivan Bratko:
  Improving Numerical Prediction with Qualitative Constraints. 385-396
  
• Cynthia A. Thompson, Roger Levy, Christopher D. Manning:
  A Generative Model for Semantic Role Labeling. 397-408
  
• Kristina Toutanova, Mark Mitchell, Christopher D. Manning:
  Optimizing Local Probability Models for Statistical Parsing. 409-420
  
• Karl Tuyls, Dries Heytens, Ann Nowé, Bernard Manderick:
  Extended Replicator Dynamics as a Key to Reinforcement Learning in Multi-agent Systems. 421-431
  
• Jarkko Venna, Samuel Kaski, Jaakko Peltonen:
  Visualizations for Assessing Convergence and Mixing of MCMC. 432-443
  
• Ricardo Vilalta, Irina Rish:
  A Decomposition of Classes via Clustering to Explain and Improve Naive Bayes. 444-455
  
• Romain Vinot, François Yvon:
  Improving Rocchio with Weakly Supervised Clustering. 456-467
  
• Nils Weidmann, Eibe Frank, Bernhard Pfahringer:
  A Two-Level Learning Method for Generalized Multi-instance Problems. 468-479
  
• Yungang Zhang, Changshui Zhang, Shijun Wang:
  Clustering in Knowledge Embedded Space. 480-491
  
• Zhi-Hua Zhou, Min-Ling Zhang:
  Ensembles of Multi-instance Learners. 492-502
  

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