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ORCID14th ECML 2003: Cavtat-Dubrovnik, Croatia
- Nada Lavrac, Dragan Gamberger, Ljupco Todorovski, Hendrik Blockeel:
Machine Learning: ECML 2003, 14th European Conference on Machine Learning, Cavtat-Dubrovnik, Croatia, September 22-26, 2003, Proceedings. Lecture Notes in Computer Science 2837, Springer 2003, ISBN 3-540-20121-1
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 F. 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. Bohté:
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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