Research
- Image and Video Retrieval
- Statistical Machine Learning
Analysis of the content of images and videos; construction of human ontology; analysis of relevance feedbacks.
Learning problems from the real world applications, such as multi-label learning, multi-task learning, and multi-instance learn; learning frameworks, such as bagging and boosting; learning algorithms, such as Support Vector Machine, Logistic Regression, and decision tree, etc.; kernel tricks.