Machine Learning: ECML 2004

Invited Papers.- Random Matrices in Data Analysis.- Data Privacy.- Breaking Through the Syntax Barrier: Searching with Entities and Relations.- Real-World Learning with Markov Logic Networks.- Strength in Diversity: The Advance of Data Analysis.- Contributed Papers.- Filtered Reinforcement Learning.- Applying Support Vector Machines to Imbalanced Datasets.- Sensitivity Analysis of the Result in Binary Decision Trees.- A Boosting Approach to Multiple Instance Learning.- An Experimental Study of Different Approaches to Reinforcement Learning in Common Interest Stochastic Games.- Learning from Message Pairs for Automatic Email Answering.- Concept Formation in Expressive Description Logics.- Multi-level Boundary Classification for Information Extraction.- An Analysis of Stopping and Filtering Criteria for Rule Learning.- Adaptive Online Time Allocation to Search Algorithms.- Model Approximation for HEXQ Hierarchical Reinforcement Learning.- Iterative Ensemble Classification for Relational Data: A Case Study of Semantic Web Services.- Analyzing Multi-agent Reinforcement Learning Using Evolutionary Dynamics.- Experiments in Value Function Approximation with Sparse Support Vector Regression.- Constructive Induction for Classifying Time Series.- Fisher Kernels for Logical Sequences.- The Enron Corpus: A New Dataset for Email Classification Research.- Margin Maximizing Discriminant Analysis.- Multi-objective Classification with Info-Fuzzy Networks.- Improving Progressive Sampling via Meta-learning on Learning Curves.- Methods for Rule Conflict Resolution.- An Efficient Method to Estimate Labelled Sample Size for Transductive LDA(QDA/MDA) Based on Bayes Risk.- Analyzing Sensory Data Using Non-linear Preference Learning with Feature Subset Selection.- Dynamic Asset Allocation Exploiting Predictors in Reinforcement Learning Framework.- Justification-Based Selection of Training Examples for Case Base Reduction.- Using Feature Conjunctions Across Examples for Learning Pairwise