— In this article we tackle the problem of scheduling a dynamically generated DAG of multi-processor tasks (M-tasks). At first, we outline the need of such a scheduling approach...
In this article, we revisit the problem of scheduling dynamically generated directed acyclic graphs (DAGs) of multi-processor tasks (M-tasks). A DAG is a basic model for expressin...
In this paper we present a family of models and learning algorithms that can simultaneously align and cluster sets of multidimensional curves measured on a discrete time grid. Our...
— Dynamic Bayesian Networks (DBNs) provide a systematic framework for robust online monitoring of dynamic systems. This paper presents an approach for increasing the efficiency ...
Indranil Roychoudhury, Gautam Biswas, Xenofon D. K...
Particle filtering (PF) for dynamic Bayesian networks (DBNs) with discrete-state spaces includes a resampling step which concentrates samples according to their relative weight in ...