We propose a novel probabilistic framework for learning
visual models of 3D object categories by combining appearance
information and geometric constraints. Objects are
represen...
Automatically categorizing documents into pre-defined topic hierarchies or taxonomies is a crucial step in knowledge and content management. Standard machine learning techniques ...
Recent work has shown the feasibility and promise of templateindependent Web data extraction. However, existing approaches use decoupled strategies ? attempting to do data record ...
Jun Zhu, Zaiqing Nie, Ji-Rong Wen, Bo Zhang, Wei-Y...
Numerous applications of data mining to scientific data involve the induction of a classification model. In many cases, the collection of data is not performed with this task in m...
Large scale learning is often realistic only in a semi-supervised setting where a small set of labeled examples is available together with a large collection of unlabeled data. In...