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» Generating Model with Uncertainty by Means of JTL
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AUTOMATICA
2010
96views more  AUTOMATICA 2010»
13 years 4 months ago
On resampling and uncertainty estimation in Linear System Identification
Linear System Identification yields a nominal model parameter, which minimizes a specific criterion based on the single inputoutput data set. Here we investigate the utility of va...
Simone Garatti, Robert R. Bitmead
ICTAI
2008
IEEE
13 years 11 months ago
A Model for Multiple Outcomes Games
We introduce and study qualitative multiple outcomes games. These games are noncooperative games with qualitative utilities (i.e., values over an ordinal scale), strictly qualitat...
Ramzi Ben Larbi, Sébastien Konieczny, Pierr...
SC
2009
ACM
13 years 11 months ago
Many task computing for multidisciplinary ocean sciences: real-time uncertainty prediction and data assimilation
Error Subspace Statistical Estimation (ESSE), an uncertainty prediction and data assimilation methodology employed for real-time ocean forecasts, is based on a characterization an...
Constantinos Evangelinos, Pierre F. J. Lermusiaux,...
DAC
2006
ACM
14 years 5 months ago
Gain-based technology mapping for minimum runtime leakage under input vector uncertainty
The gain-based technology mapping paradigm has been successfully employed for finding minimum delay and minimum area mappings. However, existing gain-based technology mappers fail...
Ashish Kumar Singh, Murari Mani, Ruchir Puri, Mich...
DAGSTUHL
2007
13 years 6 months ago
Sampling-based Approximation Algorithms for Multi-stage Stochastic Optimization
Stochastic optimization problems provide a means to model uncertainty in the input data where the uncertainty is modeled by a probability distribution over the possible realizatio...
Chaitanya Swamy, David B. Shmoys