In this paper we study a dynamic sensor selection method for Bayesian filtering problems. In particular we consider the distributed Bayesian Filtering strategy given in [1] and sh...
Jensen's inequality is a powerful mathematical tool and one of the workhorses in statistical learning. Its applications therein include the EM algorithm, Bayesian estimation ...
Abstract: The problem of modeling and assessing an individual’s ability level is central to learning environments. Numerous approaches exists to this end. Computer Adaptive Testi...
an be used to abstract away from the physical reality by describing it as components that exist in discrete states with probabilistically invoked actions that change the state. The...
Duncan Gillies, David Thornley, Chatschik Bisdikia...
We present a novel mixed-state dynamic Bayesian network (DBN) framework for modeling and classifying timeseries data such as object trajectories. A hidden Markov model (HMM) of di...
Vladimir Pavlovic, Brendan J. Frey, Thomas S. Huan...