Scope
Last modified
2007-12-16 10:47
Topics of interest include, but are not limited to,
the following:
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General Machine Learning Theory
- Statistical learning theory
- Unsupervised and Supervised Learning
- Multivariate analysis
- Hierarchical learning models
- Relational learning models
- Bayesian methods
- Meta learning
- Stochastic optimization
- Simulated annealing
- Heuristic optimization techniques
- Neural networks
- Reinforcement learning
- Multi-criteria reinforcement learning
- General Learning models
- Multiple hypothesis testing
- Decision making
- Markov chain Monte Carlo (MCMC) methods
- Non-parametric methods
- Graphical models
- Gaussian graphical models
- Bayesian networks
- Particle filter
- Cross-Entropy method
- Ant colony optimization
- Time series prediction
- Fuzzy logic and learning
- Inductive learning and applications
- Grammatical inference
General Graph-based Machine Learning Techniques
- Graph kernel and graph distance methods
- Graph-based semi-supervised learning
- Graph clustering
- Graph learning based on graph transformations
- Graph learning based on graph grammars
- Graph learning based on graph matching
- General theoretical aspects of graph learning
- Statistical modeling of graphs
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