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MP
2006
107views more  MP 2006»
13 years 8 months ago
Convergence theory for nonconvex stochastic programming with an application to mixed logit
Monte Carlo methods have been used extensively in the area of stochastic programming. As with other methods that involve a level of uncertainty, theoretical properties are required...
Fabian Bastin, Cinzia Cirillo, Philippe L. Toint
DAC
2010
ACM
13 years 9 months ago
QuickYield: an efficient global-search based parametric yield estimation with performance constraints
With technology scaling down to 90nm and below, many yield-driven design and optimization methodologies have been proposed to cope with the prominent process variation and to incr...
Fang Gong, Hao Yu, Yiyu Shi, Daesoo Kim, Junyan Re...
IPPS
2008
IEEE
14 years 3 months ago
Reducing the run-time of MCMC programs by multithreading on SMP architectures
The increasing availability of multi-core and multiprocessor architectures provides new opportunities for improving the performance of many computer simulations. Markov Chain Mont...
Jonathan M. R. Byrd, Stephen A. Jarvis, A. H. Bhal...
WCE
2007
13 years 10 months ago
Comparing Risk Neutral Density Estimation Methods using Simulated Option Data
Abstract—In this paper I use Monte Carlo simulated option data to investigate the empirical power of six Risk Neutral Density (RND) estimation techniques. Three alternative appro...
Amine Bouden
ICIP
2008
IEEE
14 years 3 months ago
Blind restoration of blurred photographs via AR modelling and MCMC
We propose a new image and blur prior model, based on nonstationary autoregressive (AR) models, and use these to blindly deconvolve blurred photographic images, using the Gibbs sa...
Tom E. Bishop, Rafael Molina, James R. Hopgood