Machine Learning: ECML 2003

1. Front Matter

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2. Invited Papers

   1. From Knowledge-Based to Skill-Based Systems: Sailing as a Machine Learning Challenge

      • Pieter Adriaans

      Pages 1-8

   2. Two-Eyed Algorithms and Problems

      • Leo Breiman

      Pages 9-9

   3. Next Generation Data Mining Tools: Power Laws and Self-similarity for Graphs, Streams and Traditional Data

      • Christos Faloutsos

      Pages 10-15

   4. Taking Causality Seriously: Propensity Score Methodology Applied to Estimate the Effects of Marketing Interventions

      • Donald B. Rubin

      Pages 16-22

3. Contributed Papers

   1. Support Vector Machines with Example Dependent Costs

      • Ulf Brefeld, Peter Geibel, Fritz Wysotzki

      Pages 23-34

   2. Abalearn: A Risk-Sensitive Approach to Self-play Learning in Abalone

      • Pedro Campos, Thibault Langlois

      Pages 35-46

   3. Life Cycle Modeling of News Events Using Aging Theory

      • Chien Chin Chen, Yao-Tsung Chen, Yeali Sun, Meng Chang Chen

      Pages 47-59

   4. Unambiguous Automata Inference by Means of State-Merging Methods

      • François Coste, Daniel Fredouille

      Pages 60-71

   5. Could Active Perception Aid Navigation of Partially Observable Grid Worlds?

      • Paul A. Crook, Gillian Hayes

      Pages 72-83

   6. Combined Optimization of Feature Selection and Algorithm Parameters in Machine Learning of Language

      • Walter Daelemans, Véronique Hoste, Fien De Meulder, Bart Naudts

      Pages 84-95

   7. Iteratively Extending Time Horizon Reinforcement Learning

      • Damien Ernst, Pierre Geurts, Louis Wehenkel

      Pages 96-107

   8. Volume under the ROC Surface for Multi-class Problems

      • César Ferri, José Hernández-Orallo, Miguel Angel Salido

      Pages 108-120

   9. Improving the AUC of Probabilistic Estimation Trees

      • César Ferri, Peter A. Flach, José Hernández-Orallo

      Pages 121-132

   10. Scaled CGEM: A Fast Accelerated EM

       • Jörg Fischer, Kristian Kersting

       Pages 133-144

   11. Pairwise Preference Learning and Ranking

       • Johannes Fürnkranz, Eyke Hüllermeier

       Pages 145-156

   12. A New Way to Introduce Knowledge into Reinforcement Learning

       • Pascal Garcia

       Pages 157-168

   13. Improvement of the State Merging Rule on Noisy Data in Probabilistic Grammatical Inference

       • Amaury Habrard, Marc Bernard, Marc Sebban

       Pages 169-180

   14. COllective INtelligence with Sequences of Actions

       • Pieter Jan ’t Hoen, Sander M. Bohte

       Pages 181-192

   15. Rademacher Penalization over Decision Tree Prunings

       • Matti Kääriäinen, Tapio Elomaa

       Pages 193-204

The proceedings of ECML/PKDD2003 are published in two volumes: the P- ceedings of the 14th European Conference on Machine Learning (LNAI 2837) and the Proceedings of the 7th European Conference on Principles and Practice of Knowledge Discovery in Databases (LNAI 2838). The two conferences were held on September 22–26, 2003 in Cavtat, a small tourist town in the vicinity of Dubrovnik, Croatia. As machine learning and knowledge discovery are two highly related ?elds, theco-locationofbothconferencesisbene?cialforbothresearchcommunities.In Cavtat, ECML and PKDD were co-located for the third time in a row, following the successful co-location of the two European conferences in Freiburg (2001) and Helsinki (2002). The co-location of ECML2003 and PKDD2003 resulted in a joint program for the two conferences, including paper presentations, invited talks, tutorials, and workshops. Out of 332 submitted papers, 40 were accepted for publication in the ECML2003proceedings,and40wereacceptedforpublicationinthePKDD2003 proceedings. All the submitted papers were reviewed by three referees. In ad- tion to submitted papers, the conference program consisted of four invited talks, four tutorials, seven workshops, two tutorials combined with a workshop, and a discovery challenge.

• Boosting
• Support Vector Machine
• algorithms
• classification
• learning
• machine learning
• reinforcement learning
• supervised learning
• algorithm analysis and problem complexity

• University of Nova Gorica, Nova Gorica, Slovenia

  Nada Lavrač

• Rudjer Bošković Institute, Zagreb, Croatia

  Dragan Gamberger

• Leiden Institute of Advanced Computer Science, Leiden University,  

  Hendrik Blockeel

• Jozef Stefan Institute, Ljubljana, Slovenia

  Ljupčo Todorovski

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