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ICML
2009
IEEE
14 years 9 months ago
Tractable nonparametric Bayesian inference in Poisson processes with Gaussian process intensities
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...
UAI
1998
13 years 10 months ago
Hierarchical Solution of Markov Decision Processes using Macro-actions
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...
NIPS
2003
13 years 10 months ago
Gaussian Processes in Reinforcement Learning
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...
Carl Edward Rasmussen, Malte Kuss
BPM
2008
Springer
147views Business» more  BPM 2008»
13 years 10 months ago
Business Process Modelling with Continuous Validation
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...
Stefan Kühne, Heiko Kern, Volker Gruhn, Ralf ...
DATE
2010
IEEE
171views Hardware» more  DATE 2010»
14 years 1 months ago
Automated bottleneck-driven design-space exploration of media processing systems
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...