The inhomogeneous Poisson process is a point process that has varying intensity across its domain (usually time or space). For nonparametric Bayesian modeling, the Gaussian proces...
Ryan Prescott Adams, Iain Murray, David J. C. MacK...
tigate the use of temporally abstract actions, or macro-actions, in the solution of Markov decision processes. Unlike current models that combine both primitive actions and macro-...
Milos Hauskrecht, Nicolas Meuleau, Leslie Pack Kae...
We exploit some useful properties of Gaussian process (GP) regression models for reinforcement learning in continuous state spaces and discrete time. We demonstrate how the GP mod...
In this paper, we demonstrate the prototype of a modelling tool that applies graph-based rules for identifying problems in business process models. The advantages of our approach a...
Abstract—Media processing systems often have limited resources and strict performance requirements. An implementation must meet those design constraints while minimizing resource...
Yang Yang, Marc Geilen, Twan Basten, Sander Stuijk...