Kernel machines have been shown as the state-of-the-art learning techniques for classification. In this paper, we propose a novel general framework of learning the Unified Kernel ...
This paper proposes a framework to aid video analysts in detecting suspicious activity within the tremendous amounts of video data that exists in today’s world of omnipresent su...
Self-propagating computer worms have been terrorizing the Internet for the last several years. With the increasing density, inter-connectivity and bandwidth of the Internet combin...
High contention of flows is associated with unstable network behavior and unmanageable resource administration, i.e., convergence to equilibrium becomes a difficult task. In this ...
This paper describes a class ofprobabilistic approximation algorithms based on bucket elimination which o er adjustable levels of accuracy ande ciency. We analyzethe approximation...