ECML-PKDD 2002

45 papers

A Kernel Approach for Learning from Almost Orthogonal Patterns Bernhard Schölkopf, Jason Weston, Eleazar Eskin, Christina S. Leslie, William Stafford Noble

A Multistrategy Approach to the Classification of Phases in Business Cycles Katharina Morik, Stefan Rüping

A Robust Boosting Algorithm Richard Nock, Patrice Lefaucheur

An Empirical Study of Encoding Schemes and Search Strategies in Discovering Causal Networks Honghua Dai, Gang Li, Yiqing Tu

An Information Geometric Perspective on Active Learning Chen-Hsiang Yeang

Boosting Density Function Estimators Franck Thollard, Marc Sebban, Philippe Ézéquel

Case Exchange Strategies in Multiagent Learning Santiago Ontañón, Enric Plaza

Characterizing Markov Decision Processes Bohdana Ratitch, Doina Precup

Class Probability Estimation and Cost-Sensitive Classification Decisions Dragos D. Margineantu

Collaborative Learning of Term-Based Concepts for Automatic Query Expansion Stefan Klink, Armin Hust, Markus Junker, Andreas Dengel

Convergent Gradient Ascent in General-Sum Games Bikramjit Banerjee, Jing Peng

Discriminative Clustering: Optimal Contingency Tables by Learning Metrics Janne Sinkkonen, Samuel Kaski, Janne Nikkilä

Evidence That Incremental Delta-Bar-Delta Is an Attribute-Efficient Linear Learner Harlan D. Harris

Finding Hidden Factors Using Independent Component Analysis Erkki Oja

How to Make AdaBoost.M1 Work for Weak Base Classifiers by Changing Only One Line of the Code Günther Eibl, Karl Peter Pfeiffer

iBoost: Boosting Using an I Nstance-Based Exponential Weighting Scheme Stephen Kwek, Chau Nguyen

Improved Smoothing for Probabilistic Suffix Trees Seen as Variable Order Markov Chains Christopher Kermorvant, Pierre Dupont

Inductive Confidence Machines for Regression Harris Papadopoulos, Kostas Proedrou, Volodya Vovk, Alex Gammerman

Learning and Inference for Clause Identification Xavier Carreras, Lluís Màrquez, Vasin Punyakanok, Dan Roth

Learning Classification with Both Labeled and Unlabeled Data Jean-Noël Vittaut, Massih-Reza Amini, Patrick Gallinari

Learning to Play a Highly Complex Game from Human Expert Games Tony Kråkenes, Ole Martin Halck

Learning with Mixture Models: Concepts and Applications Padhraic Smyth

Macro-Operators in Multirelational Learning: A Search-Space Reduction Technique Lourdes Peña Castillo, Stefan Wrobel

Multiclass Alternating Decision Trees Geoffrey Holmes, Bernhard Pfahringer, Richard Kirkby, Eibe Frank, Mark Hall

On-Line Support Vector Machine Regression Mario Martín

Pairwise Classification as an Ensemble Technique Johannes Fürnkranz

Phase Transitions and Stochastic Local Search in K-Term DNF Learning Ulrich Rückert, Stefan Kramer, Luc De Raedt

Possibilistic Induction in Decision-Tree Learning Eyke Hüllermeier

Propagation of Q-Values in Tabular TD(lambda) Philippe Preux

Q-Cut - Dynamic Discovery of Sub-Goals in Reinforcement Learning Ishai Menache, Shie Mannor, Nahum Shimkin

Ranking with Predictive Clustering Trees Ljupco Todorovski, Hendrik Blockeel, Saso Dzeroski

Reasoning with Classifiers Dan Roth

Reliable Classifications with Machine Learning Matjaz Kukar, Igor Kononenko

Revising Engineering Models: Combining Computational Discovery with Knowledge Stephen D. Bay, Daniel G. Shapiro, Pat Langley

RIONA: A Classifier Combining Rule Induction and k-NN Method with Automated Selection of Optimal Neighbourhood Grzegorz Góra, Arkadiusz Wojna

Robustness Analyses of Instance-Based Collaborative Recommendation Nicholas Kushmerick

Scaling Boosting by Margin-Based Inclusionof Features and Relations Susanne Hoche, Stefan Wrobel

Sparse Online Greedy Support Vector Regression Yaakov Engel, Shie Mannor, Ron Meir

Stacking with an Extended Set of Meta-Level Attributes and MLR Bernard Zenko, Saso Dzeroski

Support Vector Machines for Polycategorical Classification Ioannis Tsochantaridis, Thomas Hofmann

Towards a Simple Clustering Criterion Based on Minimum Length Encoding Marcus-Christopher Ludl, Gerhard Widmer

Transductive Confidence Machines for Pattern Recognition Kostas Proedrou, Ilia Nouretdinov, Volodya Vovk, Alex Gammerman

Using Hard Classifiers to Estimate Conditional Class Probabilities Ole Martin Halck

Variance Optimized Bagging Philip Derbeko, Ran El-Yaniv, Ron Meir

Variational Extensions to EM and Multinomial PCA Wray L. Buntine