10. ECML 1998: Chemnitz, Germany

@proceedings{DBLP:conf/ecml/1998,
  editor    = {Claire Nedellec and
               C{\'e}line Rouveirol},
  title     = {Machine Learning: ECML-98, 10th European Conference on Machine
               Learning, Chemnitz, Germany, April 21-23, 1998, Proceedings},
  booktitle = {ECML},
  publisher = {Springer},
  series    = {Lecture Notes in Computer Science},
  volume    = {1398},
  year      = {1998},
  isbn      = {3-540-64417-2},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}

Invited Papers

• Kenneth DeJong: Learning in Agent-Oriented Worlds (Abstract). 3 BibTeX
• David D. Lewis: Naive (Bayes) at Forty: The Independence Assumption in Information Retrieval. 4-15 BibTeX

Regular Papers

Applications of ML

• Nuno Miguel Marques, José Gabriel Pereira Lopes, Carlos Agra Coelho: Learning Verbal Transitivity Using LogLinear Models. 19-24 BibTeX
• Lluís Màrquez, Horacio Rodríguez: Part-of-Speech Tagging Using Decision Trees. 25-36 BibTeX
• François Coste, Jacques Nicolas: Inference of Finite Automata: Reducing the Search Space with an Ordering of Pairs of States. 37-42 BibTeX
• René Schneider: Automatic Acquisition of Lexical Knowledge from Sparse and Noisy Data. 43-48 BibTeX
• Sylvain Létourneau, Stan Matwin, Fazel Famili: A Normalization Method for Contextual Data: Experience from a Large-Scale Application. 49-54 BibTeX
• Claude Sammut, Tatjana Zrimec: Learning to Classify X-Ray Images Using Relational Learning. 55-60 BibTeX
• Saso Dzeroski, Nico Jacobs, Martín Molina, Carlos Moure: ILP Experiments in Detecting Traffic Problems. 61-66 BibTeX
• Filippo Neri: Simulating Children Learning and Explaining Elementary Heat Transfer Phenomena: A Multistrategy System at Work. 67-76 BibTeX

Baysesian Networks

• Petri Kontkanen, Petri Myllymäki, Tomi Silander, Henry Tirri: Bayes Optimal Instance-Based Learning. 77-88 BibTeX
• Petri Kontkanen, Petri Myllymäki, Tomi Silander, Henry Tirri, Peter Grünwald: Bayesian and Information-Theories Priors for Bayesian Network Parameters. 89-94 BibTeX

Feature Selection

• Dunja Mladenic: Feature Subset Selection in Text-Learning. 95-100 BibTeX
• Huan Liu, Hiroshi Motoda, Manoranjan Dash: A Monotonic Measure for Optimal Feature Selection. 101-106 BibTeX

Decision Trees

• Rui Camacho: Inducing Models of human Control Skills. 107-118 BibTeX
• Hilan Bensusan: God Doesn't Always Shave with Occam's Razor - Learning When and How to Prune. 119-124 BibTeX
• Luís Torgo: Error Estimators for Pruning Regression Trees. 125-130 BibTeX
• Jeffrey P. Bradford, Clayton Kunz, Ron Kohavi, Clifford Brunk, Carla E. Brodley: Pruning Decision Trees with Misclassification Costs. 131-136 BibTeX

Support Vector Learning

• Thorsten Joachims: Text Categorization with Suport Vector Machines: Learning with Many Relevant Features. 137-142 BibTeX
• Rolf Rossius, Gérard Zenker, Andreas Ittner, Werner Dilger: A Short Note About the Application of Polynomial Kernels with Fractional Degree in Support Vector Learning. 143-148 BibTeX

Multiple Models for Classification

• Murlikrishna Viswanathan, Geoffrey I. Webb: Classification Learning Using All Rules. 149-159 BibTeX
• Miguel Moreira, Eddy Mayoraz: Improved Pairwise Coupling Classification with Correcting Classifiers. 160-171 BibTeX
• Jacek Jelonek, Jerzy Stefanowski: Experiments on Solving Multiclass Learning Problems by n²-classifier. 172-177 BibTeX
• Joao Gama: Combining Classifiers by Constructive Induction. 178-189 BibTeX
• Kai Ming Ting, Zijian Zheng: Boosting Trees for Cost-Sensitive Classifications. 190-195 BibTeX
• Zijian Zheng: Naive Bayesian Classifier Committees. 196-207 BibTeX
• Petri Kontkanen, Petri Myllymäki, Tomi Silander, Henry Tirri: Batch Classification with Discrete Finite Mixtures. 208-213 BibTeX

Inductive Logic Programming

• Ute Schmid, Fritz Wysotzki: Induction of Recursive Program Schemes. 214-225 BibTeX
• Henrik Boström: Predicate Invention and Learning from Positive Examples Only. 226-237 BibTeX
• Dominique Bouthinon, Henry Soldano: An Inductive Logic Programming Framework to Learn a Concept from Ambiguous Examples. 238-249 BibTeX

Relational Learning

• Mark Craven, Seán Slattery, Kamal Nigam: First-Order Learning for Web Mining. 250-255 BibTeX
• Stefan Schrödl: Explanation-Based Generalization in Game Playing: Quantitative Results. 256-267 BibTeX

Instance Based Learning

• Nicolas Lachiche, Pierre Marquis: Scope Classification: An Instance-Based Learning Algorithm with a Rule-Based Characterisation. 268-279 BibTeX
• Francesco Ricci, David W. Aha: Error-Correcting Output Codes for Local Learners. 280-291 BibTeX
• Gianluca Bontempi, Mauro Birattari, Hugues Bersini: Recursive Lazy Learning for Modeling and Control. 292-303 BibTeX
• Engelbert Mephu Nguifo, Patrick Njiwoua: Using Lattice-Based Framework as a Tool for Feature Extraction. 304-309 BibTeX

Clustering

• João José Furtado Vasco: Determining Property Relevance in Concept Formation by Computing Correlation Between Properties. 310-315 BibTeX
• Luis Talavera, Josep Roure: A Buffering Strategy to Avoid Ordering Effects in Clustering. 316-321 BibTeX

Genetic Algorithms

• Cosimo Anglano, Attilio Giordana, Giuseppe Lo Bello, Lorenza Saitta: Coevolutionary, Distributed Search for Inducing Concept Description. 322-333 BibTeX
• Antoine Ducoulombier, Michèle Sebag: Continuous Mimetic Evolution. 334-345 BibTeX
• Björn Olsson: A Host-Parasite Genetic Algorithm for Asymmetric Tasks. 346-351 BibTeX

Reinforcement Learning

• Marco Wiering, Jürgen Schmidhuber: Speeding up Q(lambda)-Learning. 352-363 BibTeX
• Antonella Giani, Andrea Sticca, Fabrizio Baiardi, Antonina Starita: Q-Learning and Redundancy Reduction in Classifier Systems with Internal State. 364-369 BibTeX
• Chris Drummond: Composing Functions to Speed up Reinforcement Learning in a Changing World. 370-381 BibTeX
• Doina Precup, Richard S. Sutton, Satinder P. Singh: Theoretical Results on Reinforcement Learning with Temporally Abstract Options. 382-393 BibTeX
• Rémi Munos: A General Convergence Method for Reinforcement Learning in the Continuous Case. 394-405 BibTeX

Neural Networks

• Ton Weijters, Antal van den Bosch, H. Jaap van den Herik: Interpretable Neural Networks with BP-SOM. 406-411 BibTeX
• Marghny H. Mohamed, Teruya Minamoto, Koichi Niijima: Convergence Rate of Minimization Learning for Neural Networks. 412-417 BibTeX