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SIAMIS
2011
14 years 11 months ago
NESTA: A Fast and Accurate First-Order Method for Sparse Recovery
Abstract. Accurate signal recovery or image reconstruction from indirect and possibly undersampled data is a topic of considerable interest; for example, the literature in the rece...
Stephen Becker, Jérôme Bobin, Emmanue...
BMCBI
2007
194views more  BMCBI 2007»
15 years 4 months ago
Kernel-imbedded Gaussian processes for disease classification using microarray gene expression data
Background: Designing appropriate machine learning methods for identifying genes that have a significant discriminating power for disease outcomes has become more and more importa...
Xin Zhao, Leo Wang-Kit Cheung
BMCBI
2007
157views more  BMCBI 2007»
15 years 4 months ago
A hybrid multiscale Monte Carlo algorithm (HyMSMC) to cope with disparity in time scales and species populations in intracellula
Background: The fundamental role that intrinsic stochasticity plays in cellular functions has been shown via numerous computational and experimental studies. In the face of such e...
Asawari Samant, Babatunde A. Ogunnaike, Dionisios ...
SIAMSC
2011
151views more  SIAMSC 2011»
14 years 11 months ago
Inexact Newton Methods with Restricted Additive Schwarz Based Nonlinear Elimination for Problems with High Local Nonlinearity
The classical inexact Newton algorithm is an efficient and popular technique for solving large sparse nonlinear system of equations. When the nonlinearities in the system are wellb...
Xiao-Chuan Cai, Xuefeng Li
IOR
2008
91views more  IOR 2008»
15 years 4 months ago
A Randomized Quasi-Monte Carlo Simulation Method for Markov Chains
We introduce and study a randomized quasi-Monte Carlo method for estimating the state distribution at each step of a Markov chain. The number of steps in the chain can be random an...
Pierre L'Ecuyer, Christian Lécot, Bruno Tuf...