14. ECML 2002:
Helsinki, Finland
Tapio Elomaa, Heikki Mannila, Hannu Toivonen (Eds.):
Machine Learning: ECML 2002, 13th European Conference on Machine Learning, Helsinki, Finland, August 19-23, 2002, Proceedings.
Lecture Notes in Computer Science 2430 Springer 2002, ISBN 3-540-44036-4 
Contributed Papers
- Bikramjit Banerjee, Jing Peng:
Convergent Gradient Ascent in General-Sum Games.
1-9
- Stephen D. Bay, Daniel G. Shapiro, Pat Langley:
Revising Engineering Models: Combining Computational Discovery with Knowledge.
10-22
- Wray L. Buntine:
Variational Extensions to EM and Multinomial PCA.
23-34
- Xavier Carreras, Lluís Màrquez, Vasin Punyakanok, Dan Roth:
Learning and Inference for Clause Identification.
35-47
- Honghua Dai, Gang Li, Yiqing Tu:
An Empirical Study of Encoding Schemes and Search Strategies in Discovering Causal Networks.
48-59
- Philip Derbeko, Ran El-Yaniv, Ron Meir:
Variance Optimized Bagging.
60-71
- Günther Eibl, Karl Peter Pfeiffer:
How to Make AdaBoost.M1 Work for Weak Base Classifiers by Changing Only One Line of the Code.
72-83
- Yaakov Engel, Shie Mannor, Ron Meir:
Sparse Online Greedy Support Vector Regression.
84-96
- Johannes Fürnkranz:
Pairwise Classification as an Ensemble Technique.
97-110
- Grzegorz Góra, Arkadiusz Wojna:
RIONA: A Classifier Combining Rule Induction and k-NN Method with Automated Selection of Optimal Neighbourhood.
111-123
- Ole Martin Halck:
Using Hard Classifiers to Estimate Conditional Class Probabilities.
124-134
- Harlan D. Harris:
Evidence that Incremental Delta-Bar-Delta Is an Attribute-Efficient Linear Learner.
135-147
- Susanne Hoche, Stefan Wrobel:
Scaling Boosting by Margin-Based Inclusionof Features and Relations.
148-160
- Geoffrey Holmes, Bernhard Pfahringer, Richard Kirkby, Eibe Frank, Mark Hall:
Multiclass Alternating Decision Trees.
161-172
- Eyke Hüllermeier:
Possibilistic Induction in Decision-Tree Learning.
173-184
- Christopher Kermorvant, Pierre Dupont:
Improved Smoothing for Probabilistic Suffix Trees Seen as Variable Order Markov Chains.
185-194
- Stefan Klink, Armin Hust, Markus Junker, Andreas Dengel:
Collaborative Learning of Term-Based Concepts for Automatic Query Expansion.
195-206
- Tony Kråkenes, Ole Martin Halck:
Learning to Play a Highly Complex Game from Human Expert Games.
207-218
- Matjaz Kukar, Igor Kononenko:
Reliable Classifications with Machine Learning.
219-231
- Nicholas Kushmerick:
Robustness Analyses of Instance-Based Collaborative Recommendation.
232-244
- Stephen Kwek, Chau Nguyen:
iBoost: Boosting Using an i nstance-Based Exponential Weighting Scheme.
245-257
- Marcus-Christopher Ludl, Gerhard Widmer:
Towards a Simple Clustering Criterion Based on Minimum Length Encoding.
258-269
- Dragos D. Margineantu:
Class Probability Estimation and Cost-Sensitive Classification Decisions.
270-281
- Mario Martin:
On-Line Support Vector Machine Regression.
282-294
- Ishai Menache, Shie Mannor, Nahum Shimkin:
Q-Cut - Dynamic Discovery of Sub-goals in Reinforcement Learning.
295-306
- Katharina Morik, Stefan Rüping:
A Multistrategy Approach to the Classification of Phases in Business Cycles.
307-318
- Richard Nock, Patrice Lefaucheur:
A Robust Boosting Algorithm.
319-330
- Santiago Ontañón, Enric Plaza:
Case Exchange Strategies in Multiagent Learning.
331-344
- Harris Papadopoulos, Kostas Proedrou, Volodya Vovk, Alexander Gammerman:
Inductive Confidence Machines for Regression.
345-356
- Lourdes Peña Castillo, Stefan Wrobel:
Macro-Operators in Multirelational Learning: A Search-Space Reduction Technique.
357-368
- Philippe Preux:
Propagation of Q-values in Tabular TD(lambda).
369-380
- Kostas Proedrou, Ilia Nouretdinov, Volodya Vovk, Alexander Gammerman:
Transductive Confidence Machines for Pattern Recognition.
381-390
- Bohdana Ratitch, Doina Precup:
Characterizing Markov Decision Processes.
391-404
- Ulrich Rückert, Stefan Kramer, Luc De Raedt:
Phase Transitions and Stochastic Local Search in k-Term DNF Learning.
405-417
- Janne Sinkkonen, Samuel Kaski, Janne Nikkilä:
Discriminative Clustering: Optimal Contingency Tables by Learning Metrics.
418-430
- Franck Thollard, Marc Sebban, Philippe Ézéquel:
Boosting Density Function Estimators.
431-443
- Ljupco Todorovski, Hendrik Blockeel, Saso Dzeroski:
Ranking with Predictive Clustering Trees.
444-455
- Ioannis Tsochantaridis, Thomas Hofmann:
Support Vector Machines for Polycategorical Classification.
456-467
- Jean-Noël Vittaut, Massih-Reza Amini, Patrick Gallinari:
Learning Classification with Both Labeled and Unlabeled Data.
468-479
- Chen-Hsiang Yeang:
An Information Geometric Perspective on Active Learning.
480-492
- Bernard Zenko, Saso Dzeroski:
Stacking with an Extended Set of Meta-level Attributes and MLR.
493-504
Invited Papers
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