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Optimal Monte Carlo Algorithms
Sofia, Bulgari October 03-October 06
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/JVA.2006.37IEEE John Vincent Atanasoff 2006 Inte ...
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Ivan T. Dimov, Bulgarian Academy of Sciences

The question "what Monte Carlo can do and cannot do efficiently" is discussed for some functional spaces that define the regularity of the input data. Important for practical computations data classes are considered: classes of functions with bounded derivatives and H?older type conditions.

Theoretical performance analysis of some algorithms with unimprovable rate of convergence is given. Estimates of complexity of two classes of algorithms - deterministic and randomized for the solution of a class of integral equations are presented.

Index Terms:
Monte Carlo algorithms, deterministic algorithms, integral equations, unimprovable rate of convergence.
Citation:
Ivan T. Dimov, "Optimal Monte Carlo Algorithms," jva, pp.125-131, IEEE John Vincent Atanasoff 2006 International Symposium on Modern Computing (JVA'06), 2006
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