Pattern matching and analysis over network data streams is increasingly becoming an essential primitive of network monitoring systems. It is a fundamental part of most intrusion d...
The use of recommender systems in e-commerce to guide customer choices presents a privacy protection problem that is twofold. We seek to protect the privacy interests of customers...
A key challenge in recommender system research is how to effectively profile new users, a problem generally known as cold-start recommendation. Recently the idea of progressivel...
We present a Bayesian framework for learning higherorder transition models in video surveillance networks. Such higher-order models describe object movement between cameras in the...
We present a Dynamic Data Driven Application System (DDDAS) to track 2D shapes across large pose variations by learning non-linear shape manifold as overlapping, piecewise linear s...