We present a general framework for reasoning about network worms and analyzing the potency of worms within a specific network. First, we present a discussion of the life cycle of ...
Existing Recurrent Neural Networks (RNNs) are limited in their ability to model dynamical systems with nonlinearities and hidden internal states. Here we use our general framework...
In this paper, we focus on the challenge that users face in processing messages on the web posted in participatory media settings, such as blogs. It is desirable to recommend to us...
Dynamic Bayesian networks (DBNs) offer an elegant way to integrate various aspects of language in one model. Many existing algorithms developed for learning and inference in DBNs ...
We present a system for describing and solving closed queuing network models of the memory access performance of NUMA architectures. The system consists of a model description lan...