Domain adaptation is a fundamental learning problem where one wishes to use labeled data from one or several source domains to learn a hypothesis performing well on a different, y...
SVM based image retrieval suffers from the scarcity of labelled samples. In this paper, this problem is solved by incorporating prior knowledge into SVM. Firstly, some prior knowl...
The PAC-learning model is distribution-independent in the sense that the learner must reach a learning goal with a limited number of labeled random examples without any prior know...
Many documents on the Web are formated in a weakly structured format. Because of their weak semantic and because of the heterogeneity of their formats, the information conveyed by...
This paper focuses on the application of rough set constructs to inductive learning from a database. A design guideline is suggested, which provides users the option to choose app...