We address the problem of learning classifiers for several related tasks that may differ in their joint distribution of input and output variables. For each task, small
We study the potential benefits to classification prediction that arise from having access to unlabeled samples. We compare learning in the semi-supervised model to the standard, ...
Activity recognition is a hot topic in context-aware computing. In activity recognition, machine learning techniques have been widely applied to learn the activity models from lab...