Today’s Web browsers allow users to open links in new windows or tabs. This action, which we call ‘branching’, is sometimes performed on search results when the user plans t...
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...
This paper presents an adaptive algorithm for learning the user profile. The user profile is learned incrementally and continuously based on user’s initial profile, his actions ...
Abstract. This article introduces probabilistic cluster branching processes, a probabilistic unfolding semantics for untimed Petri nets, with no structural or safety assumptions, g...
The goal of this paper is to analyse semantics of algorithms with explicit continuous time with further aim to nd approaches to automatize model checking in high level, easily unde...