9. ECML 1997:
Prague,
Czech Republic
Maarten van Someren, Gerhard Widmer (Eds.):
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 BibTeX
@proceedings{DBLP:conf/ecml/1997,
editor = {Maarten van Someren and
Gerhard Widmer},
title = {Machine Learning: ECML-97, 9th European Conference on Machine
Learning, Prague, Czech Republic, April 23-25, 1997, Proceedings},
booktitle = {ECML},
publisher = {Springer},
series = {Lecture Notes in Computer Science},
volume = {1224},
year = {1997},
isbn = {3-540-62858-4},
bibsource = {DBLP, http://dblp.uni-trier.de}
}
Invited Papers
Regular Papers
- Eva Armengol, Enric Plaza:
Induction of Feature Terms With INDIE.
33-48 BibTeX
- Cristina Baroglio:
Exploiting Qualitative Knoledge to Enhance Skill Acquisition.
49-56 BibTeX
- Pawel Cichosz:
Integrated Learning and Planning Based on Truncating Temporal Differences.
57-72 BibTeX
- Luc De Raedt, Peter Idestam-Almquist, Gunther Sablon:
Theta-Subsumption for Structural Matching.
73-84 BibTeX
- Gülsen Demiröz, H. Altay Güvenir:
Classification by Voting Feature Intervals.
85-92 BibTeX
- Janez Demsar, Blaz Zupan, Marko Bohanec, Ivan Bratko:
Constructing Intermediate Concepts by Decomposition of Real Functions.
93-107 BibTeX
- Dragan Gamberger, Nada Lavrac:
Conditions for Occam's Razor Applicability and Noise Elimination.
108-123 BibTeX
- Yuh-Jyh Hu:
Learning Different Types of New Attributes by Combining the Neural Network and Iterative Attribute Construction.
124-137 BibTeX
- Alan Hutchinson:
Metrics on Terms and Clauses.
138-145 BibTeX
- Miroslav Kubat, Robert C. Holte, Stan Matwin:
Learning When Negative Examples Abound.
146-153 BibTeX
- Nicolas Lachiche, Pierre Marquis:
A Model for Generalization Based on Confirmatory Induction.
154-161 BibTeX
- Lionel Martin, Christel Vrain:
Learning Linear Constraints in Inductive Logic Programming.
162-169 BibTeX
- Rémi Munos:
Finite-Element Methods with Local Triangulation Refinement for Continuous Reimforcement Learning Problems.
170-182 BibTeX
- Nikolay I. Nikolaev, Vanio Slavov:
Inductive Genetic Programming with Decision Trees.
183-190 BibTeX
- Tim Oates, Matthew D. Schmill, Paul R. Cohen:
Parallel and Distributed Search for Structure in Multivariate Time Series.
191-198 BibTeX
- Bernhard Pfahringer:
Compression-Based Pruning of Decision Lists.
199-212 BibTeX
- Rafal Salustowicz, Jürgen Schmidhuber:
Probabilistic Incremental Program Evolution: Stochastic Search Through Program Space.
213-220 BibTeX
- Rudy Setiono, Huan Liu:
NeuroLinear: A System for Extracting Oblique Decision Rules from Neural Networks.
221-233 BibTeX
- Ning Shan, Howard J. Hamilton, Nick Cercone:
Inducing and Using Decision Rules in the GRG Knowledge Discovery System.
234-241 BibTeX
- Csaba Szepesvári:
Learning and Exploitation Do Not Conflict Under Minimax Optimality.
242-249 BibTeX
- Kai Ming Ting, Boon Toh Low:
Model Combination in the Multiple-Data-Batches Scenario.
250-265 BibTeX
- Luís Torgo, João Gama:
Search-Based Class Discretization.
266-273 BibTeX
- Fabien Torre, Céline Rouveirol:
Natural Ideal Operators in Inductive Logic Programming.
274-289 BibTeX
- Koen Vanhoof, Josée Bloemer, K. Pauwels:
A Case Study in Loyality and Satisfaction Research.
290-297 BibTeX
- Cristina Versino, Luca Maria Gambardella:
Ibots Learn Genuine Team Solutions.
298-311 BibTeX
- Ricardo Vilalta, Gunnar Blix, Larry A. Rendell:
Global Data Analysis and the Fragmentation Problem in Decision Tree Induction.
312-326 BibTeX
Workshop Position Papers
Copyright © Sat May 16 23:08:12 2009
by Michael Ley (ley@uni-trier.de)
