01 October 2014 → 30 September 2018
Regional and community funding: Special Research Fund
- Artificial intelligence
- Cognitive science and intelligent systems
fuzziness and uncertainty modelling machine learning
The goal of this project is to tackle two important and challenging problems in machine learning, namely learning from imbalanced and weakly labeled data, using the hybridization of fuzzy sets and rough sets.
A thorough study and explicit enhancement of fuzzy-rough methodologies will allow for the construction of robust new solutions tailored specifically to the problems stated above.