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ORCID9th ECML 1997: Prague, Czech Republic
- Maarten van Someren, Gerhard Widmer:
Machine Learning: ECML-97, 9th European Conference on Machine Learning, Prague, Czech Republic, April 23-25, 1997, Proceedings. Lecture Notes in Computer Science 1224, Springer 1997, ISBN 3-540-62858-4
Invited Papers
- Stuart Russell:
Uncertain Learning Agents (Abstract). 3 - Luc Stells:
Constructing and Sharing Perceptual Distiinctions. 4-13 - Paul M. B. Vitányi, Ming Li:
On Prediction by Data Compression. 14-30
Regular Papers
- Eva Armengol, Enric Plaza:
Induction of Feature Terms With INDIE. 33-48 - Cristina Baroglio:
Exploiting Qualitative Knoledge to Enhance Skill Acquisition. 49-56 - Pawel Cichosz:
Integrated Learning and Planning Based on Truncating Temporal Differences. 57-72 - Luc De Raedt
, Peter Idestam-Almquist, Gunther Sablon:
Theta-Subsumption for Structural Matching. 73-84 - Gülsen Demiröz, H. Altay Güvenir:
Classification by Voting Feature Intervals. 85-92 - Janez Demsar, Blaz Zupan, Marko Bohanec, Ivan Bratko:
Constructing Intermediate Concepts by Decomposition of Real Functions. 93-107 - Dragan Gamberger, Nada Lavrac:
Conditions for Occam's Razor Applicability and Noise Elimination. 108-123 - Yuh-Jyh Hu:
Learning Different Types of New Attributes by Combining the Neural Network and Iterative Attribute Construction. 124-137 - Alan Hutchinson:
Metrics on Terms and Clauses. 138-145 - Miroslav Kubat, Robert C. Holte, Stan Matwin:
Learning When Negative Examples Abound. 146-153 - Nicolas Lachiche, Pierre Marquis:
A Model for Generalization Based on Confirmatory Induction. 154-161 - Lionel Martin, Christel Vrain:
Learning Linear Constraints in Inductive Logic Programming. 162-169 - Rémi Munos:
Finite-Element Methods with Local Triangulation Refinement for Continuous Reimforcement Learning Problems. 170-182 - Nikolay I. Nikolaev, Vanio Slavov:
Inductive Genetic Programming with Decision Trees. 183-190 - Tim Oates, Matthew D. Schmill, Paul R. Cohen:
Parallel and Distributed Search for Structure in Multivariate Time Series. 191-198 - Bernhard Pfahringer:
Compression-Based Pruning of Decision Lists. 199-212 - Rafal Salustowicz, Jürgen Schmidhuber:
Probabilistic Incremental Program Evolution: Stochastic Search Through Program Space. 213-220 - Rudy Setiono, Huan Liu:
NeuroLinear: A System for Extracting Oblique Decision Rules from Neural Networks. 221-233 - Ning Shan, Howard J. Hamilton, Nick Cercone:
Inducing and Using Decision Rules in the GRG Knowledge Discovery System. 234-241 - Csaba Szepesvári:
Learning and Exploitation Do Not Conflict Under Minimax Optimality. 242-249 - Kai Ming Ting, Boon Toh Low:
Model Combination in the Multiple-Data-Batches Scenario. 250-265 - Luís Torgo, João Gama:
Search-Based Class Discretization. 266-273 - Fabien Torre, Céline Rouveirol:
Natural Ideal Operators in Inductive Logic Programming. 274-289 - Koen Vanhoof, Josée Bloemer, K. Pauwels:
A Case Study in Loyality and Satisfaction Research. 290-297 - Cristina Versino, Luca Maria Gambardella:
Ibots Learn Genuine Team Solutions. 298-311 - Ricardo Vilalta, Gunnar Blix, Larry A. Rendell:
Global Data Analysis and the Fragmentation Problem in Decision Tree Induction. 312-326
Workshop Position Papers
- David W. Aha, Dietrich Wettschereck:
Case-Based Learning: Beyond Classification of Feature Vectors. 329-336 - Walter Daelemans, Antal van den Bosch, Ton Weijters:
Empirical Learning of Natural Language Processing Task. 337-344 - Michael Kaiser, Volker Klingspor, Holger Friedrich:
Human-Agent Interaction and Machine Learning. 345-352 - Charles C. Taylor, Gholamreza Nakhaeizadeh:
Learning in Dynamically Changing Domains: Theory Revision and Context Dependence Issues. 353-360
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