Active learners alleviate the burden of labeling large amounts of data by detecting and asking the user to label only the most informative examples in the domain. We focus here on...
Recent advances in computer vision and pattern recognition have fuelled numerous initiatives that aim to intelligently recognize human activities. In this paper, we propose an algo...
The UCSD ActiveCampus project is an exploration of wireless location-aware computing in the university setting. ActiveClass supports classroom activities such as anonymous asking ...
William G. Griswold, Patricia Shanahan, Steven W. ...
Abstract We present an active learning framework that predicts the tradeoff between the effort and information gain associated with a candidate image annotation, thereby ranking un...
—In biomedical data, the imbalanced data problem occurs frequently and causes poor prediction performance for minority classes. It is because the trained classifiers are mostly d...