— We propose a randomized data mining method that finds clusters of spatially overlapping images. The core of the method relies on the min-Hash algorithm for fast detection of p...
In this paper, we study a novel problem Collective Active Learning, in which we aim to select a batch set of "informative" instances from a networking data set to query ...
—In this paper, we present a UML metamodel-based approach for creating and executing workflow models. The modeling language is introduced through its abstract syntax, and an eval...
We present a new active learning approach to incorporate
human feedback for on-line unusual event detection. In contrast to most
existing unsupervised methods that perform passiv...