Machine learning : ECML 2004 : 15th European Conference on Machine Learning, Pisa, Italy, September 20-24, 2004 : proceedings
Gardado en:
| Autor Principal: | |
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| Autor Corporativo: | |
| Outros autores: | , |
| Formato: | Livre numérique |
| Idioma: | Anglais |
| Publicado: |
Berlin [etc.] :
Springer
[20..].
Cham : Springer Nature |
| Series: | Lecture notes in computer science. Lecture notes in artificial intelligence
3201 |
| Sujets: | |
| Acceso en liña: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Nota: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Machine learning, ECML 2004, 15th European Conference on Machine Learning, Pisa, Italy, September 20-24, 2004, Jean-Francois Boulicaut, Floriana Esposito, Fosca Giannotti ... [et al.] (eds.), Berlin, Springer, 2004, 1 vol. (XVIII-580 p.), Lecture notes in computer science, 3-540-23105-6 • Machine Learning: ECML 2004, Texte imprimé, 9783662183670 |
Table des matières:
- 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 RelationalData: 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 Classifiers
- Feature Selection Filters Based on the Permutation Test
- Sparse Distributed Memories for On-Line Value-Based Reinforcement Learning
- Improving Random Forests
- The Principal Components Analysis of a Graph, and Its Relationships to Spectral Clustering
- Using String Kernels to Identify Famous Performers from Their Playing Style
- Associative Clustering
- Learning to Fly Simple and Robust
- Bayesian Network Methods for Traffic Flow Forecasting with Incomplete Data
- Matching Model Versus Single Model: A Study of the Requirement to Match Class Distribution Using Decision Trees
- Inducing Polynomial Equations for Regression
- Efficient Hyperkernel Learning Using Second-Order Cone Programming
- Effective Voting of Heterogeneous Classifiers
- Convergence and Divergence in Standard and Averaging Reinforcement Learning
- Document Representation for One-Class SVM
- Naive Bayesian Classifiers for Ranking
- Conditional Independence Trees
- Exploiting Unlabeled Data in Content-BasedImage Retrieval
- Population Diversity in Permutation-Based Genetic Algorithm
- Simultaneous Concept Learning of Fuzzy Rules
- Posters
- SWITCH: A Novel Approach to Ensemble Learning for Heterogeneous Data
- Estimating Attributed Central Orders
- Batch Reinforcement Learning with State Importance
- Explicit Local Models: Towards Optimal Optimization Algorithms
- An Intelligent Model for the Signorini Contact Problem in Belt Grinding Processes
- Cluster-Grouping: From Subgroup Discovery to Clustering.