Most existing semi-supervised learning methods are based on the smoothness assumption that data points in the same high density region should have the same label. This assumption, ...
Active learning methods have been considered with increased interest in the statistical learning community. Initially developed within a classification framework, a lot of extensio...
A fundamental problem in computer vision (CV) is the estimation of geometric parameters from multiple observations obtained from images; examples of such problems range from ellip...
A common trait of background subtraction algorithms is that they have learning rates, thresholds, and initial values that are hand-tuned for a scenario in order to produce the des...
Data broadcasting is well known for its excellent scalability. Multi-dimensional range queries, such as spatial range queries of geographical information for location dependent se...