Continuous-time Bayesian networks is a natural structured representation language for multicomponent stochastic processes that evolve continuously over time. Despite the compact r...
An overview is provided of recent developments in the use of latent class (LC) models in social science research. Special attention is paid to the application of LC analysis as a f...
Estimating models for both plant and disturbance dynamics is important in control design applications that focus on disturbance rejection. Several methods for low-order approximat...
In this paper, we propose GAD (General Activity Detection) for fast clustering on large scale data. Within this framework we design a set of algorithms for different scenarios: (...
Jiawei Han, Liangliang Cao, Sangkyum Kim, Xin Jin,...
A key challenge in supporting data-driven scientific applications is the storage and management of input and output data in a distributed environment. In this paper, we describe a...
Stephen Langella, Shannon Hastings, Scott Oster, T...