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» Abstraction Augmented Markov Models
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TSP
2008
103views more  TSP 2008»
15 years 1 months ago
Low-Rank Variance Approximation in GMRF Models: Single and Multiscale Approaches
Abstract--We present a versatile framework for tractable computation of approximate variances in large-scale Gaussian Markov random field estimation problems. In addition to its ef...
Dmitry M. Malioutov, Jason K. Johnson, Myung Jin C...
CMSB
2010
Springer
14 years 9 months ago
Stochasticity in reactions: a probabilistic Boolean modeling approach
Boolean modeling frameworks have long since proved their worth for capturing and analyzing essential characteristics of complex systems. Hybrid approaches aim at exploiting the ad...
Sven Twardziok, Heike Siebert, Alexander Heyl
ICML
1998
IEEE
16 years 2 months ago
Intra-Option Learning about Temporally Abstract Actions
tion Learning about Temporally Abstract Actions Richard S. Sutton Department of Computer Science University of Massachusetts Amherst, MA 01003-4610 rich@cs.umass.edu Doina Precup D...
Richard S. Sutton, Doina Precup, Satinder P. Singh
FSTTCS
2004
Springer
15 years 7 months ago
Verifying Probabilistic Procedural Programs
Abstract. Monolithic finite-state probabilistic programs have been abstractly modeled by finite Markov chains, and the algorithmic verification problems for them have been inves...
Javier Esparza, Kousha Etessami
105
Voted
FORMATS
2003
Springer
15 years 7 months ago
Discrete-Time Rewards Model-Checked
Abstract. This paper presents a model-checking approach for analyzing discrete-time Markov reward models. For this purpose, the temporal logic probabilistic CTL is extended with re...
Suzana Andova, Holger Hermanns, Joost-Pieter Katoe...