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  Browse All Reviews > Mathematics Of Computing (G) > Numerical Analysis (G.1) > Quadrature And Numerical Differentiation (G.1.4) > Iterative Methods (G.1.4...)  
  1-7 of 7 Reviews about "Iterative Methods (G.1.4...)": Date Reviewed
  iMapReduce: a distributed computing framework for iterative computation
Zhang Y., Gao Q., Gao L., Wang C.  Journal of Grid Computing 10(1): 47-68, 2020. Type: Article

MapReduce is one of the most popular standard algorithms in distributed processing. This paper contributes to performance improvement in MapReduce, which otherwise performs low on social networking and web-based data due to iterative processing. T...

Sep 28 2021
   Fractal interpolation functions with variable parameters and their analytical properties
Wang H., Yu J.  Journal of Approximation Theory 1751-18, 2013. Type: Article

A fractal interpolation function (FIF) f is a special type of continuous function that interpolates a given set of data {(xi, f(x
Dec 19 2013
   Hard thresholding pursuit: an algorithm for compressive sensing
Foucart S.  SIAM Journal on Numerical Analysis 49(6): 2543-2563, 2011. Type: Article

Compressive sensing (CS) is an exciting new model for signal processing. The author presents a new reconstruction algorithm, which is the main thrust of current CS research....

Feb 15 2013
  Increasing the locality of iterative methods and its application to the simulation of semiconductor devices
Pichel J., Heras D., Cabaleiro J., García-Loureiro A., Rivera F.  International Journal of High Performance Computing Applications 24(2): 136-153, 2010. Type: Article

Many scientific programming applications are based on computational models involving nonlinear partial differential equations. These equations are solved via discretization approaches such as the finite element method. The resulting equations lead...

Jul 28 2010
  PyTrilinos: high-performance distributed-memory solvers for Python
Sala M., Spotz W., Heroux M.  ACM Transactions on Mathematical Software 34(2): 1-33, 2008. Type: Article

The development of high-performance subroutine packages for scientific computing frequently takes place in a tension field between a number of mutually exclusive objectives. The most important goals are probably speed and efficiency on the one han...

Apr 30 2008
  Adjusting the outputs of a classifier to new a priori probabilities: a simple procedure
Saerens M., Latinne P., Decaestecker C.  Neural Computation 14(1): 21-41, 2002. Type: Article

A classifier that is trained on a data set often provides estimates of the posterior probabilities that are not valid for real world data. In this paper, the authors present a simple and original procedure for adjusting the outputs of the trained ...

May 29 2003
  Fractals everywhere
Barnsley M.,  Academic Press Prof., Inc., San Diego, CA, 1988.Type: Book (9789780120790623)

This book is based on a course called “Fractal Geometry,” which has been taught in the School of Mathematics at the Georgia Institute of Technology. It is a rigorous and attractive textbook that covers the methods and theory of determi...

Nov 1 1989
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