15. ECML 2004: Pisa, Italy
Jean-François Boulicaut, Floriana Esposito, Fosca Giannotti, Dino Pedreschi (Eds.): Machine Learning: ECML 2004, 15th European Conference on Machine Learning, Pisa, Italy, September 20-24, 2004, Proceedings. Springer 2004 Lecture Notes in Computer Science ISBN 3-540-23105-6
Invited Papers
- Dimitris Achlioptas: Random Matrices in Data Analysis. 1-7
- Rakesh Agrawal: Data Privacy. 8
- Soumen Chakrabarti: Breaking Through the Syntax Barrier: Searching with Entities and Relations. 9-16
- Pedro Domingos: Real-World Learning with Markov Logic Networks. 17
- David J. Hand: Strength in Diversity: The Advance of Data Analysis. 18-26
Contributed Papers
- Douglas Aberdeen: Filtered Reinforcement Learning. 27-38
- Rehan Akbani, Stephen Kwek, Nathalie Japkowicz: Applying Support Vector Machines to Imbalanced Datasets. 39-50
- Isabelle Alvarez: Sensitivity Analysis of the Result in Binary Decision Trees. 51-62
- Avi Bab, Ronen I. Brafman: An Experimental Study of Different Approaches to Reinforcement Learning in Common Interest Stochastic Games. 75-86
- Nicola Fanizzi, Luigi Iannone, Ignazio Palmisano, Giovanni Semeraro: Concept Formation in Expressive Description Logics. 99-110
- Aidan Finn, Nicholas Kushmerick: Multi-level Boundary Classification for Information Extraction. 111-122
- Johannes Fürnkranz, Peter A. Flach: An Analysis of Stopping and Filtering Criteria for Rule Learning. 123-133
- Matteo Gagliolo, Viktor Zhumatiy, Jürgen Schmidhuber: Adaptive Online Time Allocation to Search Algorithms. 134-143
- Bernhard Hengst: Model Approximation for HEXQ Hierarchical Reinforcement Learning. 144-155
- Andreas Heß, Nicholas Kushmerick: Iterative Ensemble Classification for Relational Data: A Case Study of Semantic Web Services. 156-167
- Pieter Jan't Hoen, Karl Tuyls: Analyzing Multi-agent Reinforcement Learning Using Evolutionary Dynamics. 168-179
- Tobias Jung, Thomas Uthmann: Experiments in Value Function Approximation with Sparse Support Vector Regression. 180-191
- Bryan Klimt, Yiming Yang: The Enron Corpus: A New Dataset for Email Classification Research. 217-226
- Mark Last: Multi-objective Classification with Info-Fuzzy Networks. 239-249
- Rui Leite, Pavel Brazdil: Improving Progressive Sampling via Meta-learning on Learning Curves. 250-261
- Tony Lindgren: Methods for Rule Conflict Resolution. 262-273
- Han Liu, Xiaobin Yuan, Qianying Tang, Rafal Kustra: An Efficient Method to Estimate Labelled Sample Size for Transductive LDA(QDA/MDA) Based on Bayes Risk. 274-285
- Oscar Luaces, Gustavo F. Bayón, José Ramón Quevedo, Jorge Díez, Juan José del Coz, Antonio Bahamonde: Analyzing Sensory Data Using Non-linear Preference Learning with Feature Subset Selection. 286-297
- Jangmin O, Jae Won Lee, Jongwoo Lee, Byoung-Tak Zhang: Dynamic Asset Allocation Exploiting Predictors in Reinforcement Learning Framework. 298-309
- Santiago Ontañón, Enric Plaza: Justification-Based Selection of Training Examples for Case Base Reduction. 310-321
- Satoshi Oyama, Christopher D. Manning: Using Feature Conjunctions Across Examples for Learning Pairwise Classifiers. 322-333
- Predrag Radivojac, Zoran Obradovic, A. Keith Dunker, Slobodan Vucetic: Feature Selection Filters Based on the Permutation Test. 334-346
- Bohdana Ratitch, Doina Precup: Sparse Distributed Memories for On-Line Value-Based Reinforcement Learning. 347-358
- Marko Robnik-Sikonja: Improving Random Forests. 359-370
- Marco Saerens, François Fouss, Luh Yen, Pierre Dupont: The Principal Components Analysis of a Graph, and Its Relationships to Spectral Clustering. 371-383
- Craig Saunders, David R. Hardoon, John Shawe-Taylor, Gerhard Widmer: Using String Kernels to Identify Famous Performers from Their Playing Style. 384-395
- Shiliang Sun, Changshui Zhang, Guoqiang Yu, Naijiang Lu, Fei Xiao: Bayesian Network Methods for Traffic Flow Forecasting with Incomplete Data. 419-428
- Kai Ming Ting: Matching Model Versus Single Model: A Study of the Requirement to Match Class Distribution Using Decision Trees. 429-440
- Ljupco Todorovski, Peter Ljubic, Saso Dzeroski: Inducing Polynomial Equations for Regression. 441-452
- Ivor W. Tsang, James T. Kwok: Efficient Hyperkernel Learning Using Second-Order Cone Programming. 453-464
- Grigorios Tsoumakas, Ioannis Katakis, Ioannis P. Vlahavas: Effective Voting of Heterogeneous Classifiers. 465-476
- Marco Wiering: Convergence and Divergence in Standard and Averaging Reinforcement Learning. 477-488
- Zhi-Hua Zhou, Ke-Jia Chen, Yuan Jiang: Exploiting Unlabeled Data in Content-Based Image Retrieval. 525-536
Posters
- Toshihiro Kamishima, Hideto Kazawa, Shotaro Akaho: Estimating Attributed Central Orders: An Empirical Comparison. 563-565
- Lihong Li, Vadim Bulitko, Russell Greiner: Batch Reinforcement Learning with State Importance. 566-568
- Jan Poland: Explicit Local Models: Towards "Optimal" Optimization Algorithms. 569-571
- Xiang Zhang, Bernd Kuhlenkötter, Klaus Kneupner: An Intelligent Model for the Signorini Contact Problem in Belt Grinding Processes. 572-574
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