Topics
AI Foundations
- Machine Learning and Data Mining
- Evolutionary computing, Bayesian and Neural Networks
- Pre-processing, Dimension Reduction and Feature Selection
- Decision/Utility Theory and Decision Optimization
- Learning Graphical Models and Complex Networks
- Search, SAT, and CSP Active, Cost-Sensitive, Semi-Supervised, Multi-Instance, Multi-Label and Multi-Task Learning
- Description Logic and Ontologies
- Transfer/Adaptive, Rational and Structured Learning
AI in Domain-specific Applications
- Preference/Ranking, Ensemble, and Reinforcement Learning
AI in Computational Biology, Medicine and Biomedical Applications
- Knowledge Representation, Reasoning and Cognitive Modelling
