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MLMTA'06: Scope
Last modified
2007-12-02 07:43
Topics of interest include, but are not limited to,
the following:
- Machine learning in problem solving
- Learning models
- Artificial neural networks and learning
- Fuzzy logic and learning
- Inductive learning and applications
- Learning by examples
- Statistical methods in learning
- Evolutionary algorithms in learning
- Reinforcement learning methods
- Multi-agent learning
- Hierarchical learning models
- Collaborative learning and filtering
- ODE Methods and machine learning
- Multi-criteria reinforcement learning
- Relational learning models
- Speedup learning techniques
- Computational needs of learning models
- Formal learning methods
- Graph-based learning
- Learning based on adaptive techniques
- Learning topological maps
- Learning in planning
- Query learning
- Active learning
- Memory-based learning
- Instance-based learning
- Life-long learning
- Q-Learning
- Predictive learning models
- Information retrieval and data mining
- Knowledge representation and management
- Knowledge acquisition and discovery techniques
- Bayesian-based methodologies
- Grammatical inference
- Cognitive modeling
- Case-based reasoning
- Semantic indexing
- Natural language processing
- Machine translation
- Temporal abstractions
- Feature selection and classification
- Theory refinement methodologies
- Probabilistic reasoning
- Self-adaptation techniques
- Game playing (chess, ...)
- Text categorization and classification
- Machine learning applications (medicine, games, biology,
industrial applications, robotics, security and terrorism, ...)
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