Machine Learning: ECML 2002: 13th European Conference on Machine Learning Helsinki, Finland, August 19–23, 2002 Proceedings

✍ Scribed by Bikramjit Banerjee, Jing Peng (auth.), Tapio Elomaa, Heikki Mannila, Hannu Toivonen (eds.)

• Publisher: Springer-Verlag Berlin Heidelberg
• Year: 2002
• Tongue: English
• Leaves: 547
• Series: Lecture Notes in Computer Science 2430 : Lecture Notes in Artificial Intelligence
• Edition: 1
• Category: Library

✦ Synopsis

This book constitutes the refereed preceedings of the 13th European Conference on Machine Learning, ECML 2002, held in Helsinki, Finland in August 2002.
The 41 revised full papers presented together with 4 invited contributions were carefully reviewed and selected from numerous submissions. Among the topics covered are computational discovery, search strategies, Classification, support vector machines, kernel methods, rule induction, linear learning, decision tree learning, boosting, collaborative learning, statistical learning, clustering, instance-based learning, reinforcement learning, multiagent learning, multirelational learning, Markov decision processes, active learning, etc.

✦ Table of Contents

Convergent Gradient Ascent in General-Sum Games....Pages 1-9
Revising Engineering Models: Combining Computational Discovery with Knowledge....Pages 10-22
Variational Extensions to EM and Multinomial PCA....Pages 23-34
Learning and Inference for Clause Identification....Pages 35-47
An Empirical Study of Encoding Schemes and Search Strategies in Discovering Causal Networks....Pages 48-59
Variance Optimized Bagging....Pages 60-72
How to Make AdaBoost.M1 Work for Weak Base Classifiers by Changing Only One Line of the Code....Pages 72-83
Sparse Online Greedy Support Vector Regression....Pages 84-96
Pairwise Classification as an Ensemble Technique....Pages 97-110
RIONA: A Classifier Combining Rule Induction and k-NN Method with Automated Selection of Optimal Neighbourhood....Pages 111-123
Using Hard Classifiers to Estimate Conditional Class Probabilities....Pages 124-134
Evidence that Incremental Delta-Bar-Delta Is an Attribute-Efficient Linear Learner....Pages 135-147
Scaling Boosting by Margin-Based Inclusion of Features and Relations....Pages 148-160
Multiclass Alternating Decision Trees....Pages 161-172
Possibilistic Induction in Decision-Tree Learning....Pages 173-184
Improved Smoothing for Probabilistic Suffix Trees Seen as Variable Order Markov Chains....Pages 185-194
Collaborative Learning of Term-Based Concepts for Automatic Query Expansion....Pages 195-207
Learning to Play a Highly Complex Game from Human Expert Games....Pages 207-218
Reliable Classifications with Machine Learning....Pages 219-231
Robustness Analyses of Instance-Based Collaborative Recommendation....Pages 232-244
i Boost: Boosting Using an i nstance-Based Exponential Weighting Scheme....Pages 245-257
Towards a Simple Clustering Criterion Based on Minimum Length Encoding....Pages 258-270
Class Probability Estimation and Cost-Sensitive Classification Decisions....Pages 270-281
On-Line Support Vector Machine Regression....Pages 282-294
Q-Cut—Dynamic Discovery of Sub-goals in Reinforcement Learning....Pages 295-306
A Multistrategy Approach to the Classification of Phases in Business Cycles....Pages 307-318
A Robust Boosting Algorithm....Pages 319-331
Case Exchange Strategies in Multiagent Learning....Pages 331-344
Inductive Confidence Machines for Regression....Pages 345-356
Macro-Operators in Multirelational Learning: A Search-Space Reduction Technique....Pages 357-368
Propagation of Q-values in Tabular TD(λ)....Pages 369-380
Transductive Confidence Machines for Pattern Recognition....Pages 381-390
Characterizing Markov Decision Processes....Pages 391-404
Phase Transitions and Stochastic Local Search in k-Term DNF Learning....Pages 405-417
Discriminative Clustering: Optimal Contingency Tables by Learning Metrics....Pages 418-430
Boosting Density Function Estimators....Pages 431-443
Ranking with Predictive Clustering Trees....Pages 444-455
Support Vector Machines for Polycategorical Classification....Pages 456-467
Learning Classification with Both Labeled and Unlabeled Data....Pages 468-479
An Information Geometric Perspective on Active Learning....Pages 480-492
Stacking with an Extended Set of Meta-level Attributes and MLR....Pages 493-504
Finding Hidden Factors Using Independent Component Analysis....Pages 505-505
Reasoning with Classifiers....Pages 506-510
A Kernel Approach for Learning from almost Orthogonal Patterns....Pages 511-528
Learning with Mixture Models: Concepts and Applications....Pages 529-529

✦ Subjects

Artificial Intelligence (incl. Robotics); Algorithm Analysis and Problem Complexity; Mathematical Logic and Formal Languages