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.
Lecture Notes in Computer Science 3201 Springer 2004, ISBN 3-540-23105-6 BibTeX
Invited Papers
Contributed Papers
- Douglas Aberdeen:
Filtered Reinforcement Learning.
27-38
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- Rehan Akbani, Stephen Kwek, Nathalie Japkowicz:
Applying Support Vector Machines to Imbalanced Datasets.
39-50
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- Isabelle Alvarez:
Sensitivity Analysis of the Result in Binary Decision Trees.
51-62
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- Peter Auer, Ronald Ortner:
A Boosting Approach to Multiple Instance Learning.
63-74
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- Avi Bab, Ronen I. Brafman:
An Experimental Study of Different Approaches to Reinforcement Learning in Common Interest Stochastic Games.
75-86
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- Steffen Bickel, Tobias Scheffer:
Learning from Message Pairs for Automatic Email Answering.
87-98
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- Nicola Fanizzi, Luigi Iannone, Ignazio Palmisano, Giovanni Semeraro:
Concept Formation in Expressive Description Logics.
99-110
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- Aidan Finn, Nicholas Kushmerick:
Multi-level Boundary Classification for Information Extraction.
111-122
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- Johannes Fürnkranz, Peter A. Flach:
An Analysis of Stopping and Filtering Criteria for Rule Learning.
123-133
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- Matteo Gagliolo, Viktor Zhumatiy, Jürgen Schmidhuber:
Adaptive Online Time Allocation to Search Algorithms.
134-143
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- Bernhard Hengst:
Model Approximation for HEXQ Hierarchical Reinforcement Learning.
144-155
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- Andreas Heß, Nicholas Kushmerick:
Iterative Ensemble Classification for Relational Data: A Case Study of Semantic Web Services.
156-167
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- Pieter Jan't Hoen, Karl Tuyls:
Analyzing Multi-agent Reinforcement Learning Using Evolutionary Dynamics.
168-179
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- Tobias Jung, Thomas Uthmann:
Experiments in Value Function Approximation with Sparse Support Vector Regression.
180-191
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- Mohammed Waleed Kadous, Claude Sammut:
Constructive Induction for Classifying Time Series.
192-204
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- Kristian Kersting, Thomas Gärtner:
Fisher Kernels for Logical Sequences.
205-216
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- Bryan Klimt, Yiming Yang:
The Enron Corpus: A New Dataset for Email Classification Research.
217-226
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- András Kocsor, Kornél Kovács, Csaba Szepesvári:
Margin Maximizing Discriminant Analysis.
227-238
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- Mark Last:
Multi-objective Classification with Info-Fuzzy Networks.
239-249
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- Rui Leite, Pavel Brazdil:
Improving Progressive Sampling via Meta-learning on Learning Curves.
250-261
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- Tony Lindgren:
Methods for Rule Conflict Resolution.
262-273
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- 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
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- 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
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- Jangmin O, Jae Won Lee, Jongwoo Lee, Byoung-Tak Zhang:
Dynamic Asset Allocation Exploiting Predictors in Reinforcement Learning Framework.
298-309
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- Santiago Ontañón, Enric Plaza:
Justification-Based Selection of Training Examples for Case Base Reduction.
310-321
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- Satoshi Oyama, Christopher D. Manning:
Using Feature Conjunctions Across Examples for Learning Pairwise Classifiers.
322-333
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- Predrag Radivojac, Zoran Obradovic, A. Keith Dunker, Slobodan Vucetic:
Feature Selection Filters Based on the Permutation Test.
334-346
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- Bohdana Ratitch, Doina Precup:
Sparse Distributed Memories for On-Line Value-Based Reinforcement Learning.
347-358
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- Marko Robnik-Sikonja:
Improving Random Forests.
359-370
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- Marco Saerens, François Fouss, Luh Yen, Pierre Dupont:
The Principal Components Analysis of a Graph, and Its Relationships to Spectral Clustering.
371-383
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- Craig Saunders, David R. Hardoon, John Shawe-Taylor, Gerhard Widmer:
Using String Kernels to Identify Famous Performers from Their Playing Style.
384-395
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- Janne Sinkkonen, Janne Nikkilä, Leo Lahti, Samuel Kaski:
Associative Clustering.
396-406
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- Dorian Suc, Ivan Bratko, Claude Sammut:
Learning to Fly Simple and Robust.
407-418
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- Shiliang Sun, Changshui Zhang, Guoqiang Yu, Naijiang Lu, Fei Xiao:
Bayesian Network Methods for Traffic Flow Forecasting with Incomplete Data.
419-428
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- Kai Ming Ting:
Matching Model Versus Single Model: A Study of the Requirement to Match Class Distribution Using Decision Trees.
429-440
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- Ljupco Todorovski, Peter Ljubic, Saso Dzeroski:
Inducing Polynomial Equations for Regression.
441-452
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- Ivor W. Tsang, James T. Kwok:
Efficient Hyperkernel Learning Using Second-Order Cone Programming.
453-464
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- Grigorios Tsoumakas, Ioannis Katakis, Ioannis P. Vlahavas:
Effective Voting of Heterogeneous Classifiers.
465-476
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- Marco Wiering:
Convergence and Divergence in Standard and Averaging Reinforcement Learning.
477-488
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- Xiaoyun Wu, Rohini K. Srihari, Zhaohui Zheng:
Document Representation for One-Class SVM.
489-500
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- Harry Zhang, Jiang Su:
Naive Bayesian Classifiers for Ranking.
501-512
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- Harry Zhang, Jiang Su:
Conditional Independence Trees.
513-524
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- Zhi-Hua Zhou, Ke-Jia Chen, Yuan Jiang:
Exploiting Unlabeled Data in Content-Based Image Retrieval.
525-536
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- Kenny Qili Zhu, Ziwei Liu:
Population Diversity in Permutation-Based Genetic Algorithm.
537-547
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- Jacobus van Zyl, Ian Cloete:
Simultaneous Concept Learning of Fuzzy Rules.
548-559
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Posters
Copyright © Sat May 16 23:08:13 2009
by Michael Ley (ley@uni-trier.de)
