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ORCID13th ECML 2002: Helsinki, Finland
- Tapio Elomaa, Heikki Mannila, Hannu Toivonen:
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 Martín:
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, Alex 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, Alex 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
- Erkki Oja:
Finding Hidden Factors Using Independent Component Analysis. 505 - Dan Roth:
Reasoning with Classifiers. 506-510 - Bernhard Schölkopf, Jason Weston, Eleazar Eskin, Christina S. Leslie, William Stafford Noble:
A Kernel Approach for Learning from almost Orthogonal Patterns. 511-528 - Padhraic Smyth:
Learning with Mixture Models: Concepts and Applications. 529-
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