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WSC
1998
13 years 8 months ago
Input Modeling Tools for Complex Problems
A simulation model is composed of inputs and logic; the inputs represent the uncertainty or randomness in the system, while the logic determines how the system reacts to the uncer...
Barry L. Nelson, Michael Yamnitsky
ICML
2007
IEEE
14 years 8 months ago
Percentile optimization in uncertain Markov decision processes with application to efficient exploration
Markov decision processes are an effective tool in modeling decision-making in uncertain dynamic environments. Since the parameters of these models are typically estimated from da...
Erick Delage, Shie Mannor
BC
2004
91views more  BC 2004»
13 years 7 months ago
Simulation and parameter estimation of dynamics of synaptic depression
Abstract. Synaptic release was simulated using a Simulink sequential storage model with three vesicular pools. Modeling was modular and easily extendable to the systems with greate...
F. Aristizabal, M. I. Glavinovic
WSC
1998
13 years 8 months ago
Bayesian Model Selection when the Number of Components is Unknown
In simulation modeling and analysis, there are two situations where there is uncertainty about the number of parameters needed to specify a model. The first is in input modeling w...
Russell C. H. Cheng
DAC
2006
ACM
14 years 8 months ago
Statistical timing based on incomplete probabilistic descriptions of parameter uncertainty
Existing approaches to timing analysis under uncertainty are based on restrictive assumptions. Statistical STA techniques assume that the full probabilistic distribution of parame...
Wei-Shen Wang, Vladik Kreinovich, Michael Orshansk...