: In this paper, we present a sampling-based verification algorithm for continuous dynamic systems with uncertainty due to adversaries, unmodeled disturbance inputs, unknown parame...
This paper is concerned with developing an information-theoretic framework to aggregate the state space of a Hidden Markov Model (HMM) on discrete state and observation spaces. The...
This work deals with trajectory optimization for a network of robotic sensors sampling a spatio-temporal random field. We examine the problem of minimizing over the space of networ...
Abstract. We develop a Bayesian approach to concept learning for crowdsourcing applications. A probabilistic belief over possible concept definitions is maintained and updated acc...
Paolo Viappiani, Sandra Zilles, Howard J. Hamilton...
Abstract. Advances in sensing and satellite technologies and the growth of Internet have resulted in the easy accessibility of vast amount of spatial data. Extracting useful knowle...
Chang Sheng, Wynne Hsu, Mong Lee, Anthony K. H. Tu...