Compositional model theory serves as an alternative approach to multidimensional probability distribution representation and processing. Every compositional model over a finite non-empty set of variables N is uniquely defined by its generating sequence – an ordered set of low-dimensional probability distributions. A generating sequence structure induces a system of conditional independence stat...

In real-time software, not only computation errors but also timing errors can cause system failures, which eventually result in significant physical damages or threats to human life. To efficiently guarantee the timely execution of expected functions, it is necessary to clearly specify and formally verify timing requirements before performing detailed system design. This paper proposes a compos...

The focus of the action understanding literature has predominately been classification, however, there are many applications demanding richer action understanding such as mobile robotics and video search, with solutions to classification, localization and detection. In this paper, we propose a compositional model that leverages a new mid-level representation called compositional trajectories an...