The estimation of linear causal models (also known as structural equation models) from data is a well-known problem which has received much attention in the past. Most previous wo...
Patrik O. Hoyer, Shohei Shimizu, Antti J. Kerminen
Abstract. Digital signal processing and control (DSPC) tools allow application developers to assemble systems by connecting predefined components in signal–flow graphs and by h...
A Bayesian belief network is a model of a joint distribution over a finite set of variables, with a DAG structure representing immediate dependencies among the variables. For each...
Abstract. We consider the problem of estimating vector-valued variables from noisy "relative" measurements. The measurement model can be expressed in terms of a graph, wh...
Prabir Barooah, Neimar Machado da Silva, Joã...
This paper proposes an approach for solving the problem of composite process oriented service discovery with preserving business and timed relation. Key to our approach is the def...