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292
QuasiRandom Sequences and Their Discrepancies
 SIAM J. Sci. Comput
, 1994
"... Quasirandom (also called low discrepancy) sequences are a deterministic alternative to random sequences for use in Monte Carlo methods, such as integration and particle simulations of transport processes. The error in uniformity for such a sequence of N points in the sdimensional unit cube is meas ..."
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Cited by 95 (6 self)
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Quasirandom (also called low discrepancy) sequences are a deterministic alternative to random sequences for use in Monte Carlo methods, such as integration and particle simulations of transport processes. The error in uniformity for such a sequence of N points in the sdimensional unit cube
QUASIRANDOM SEQUENCES AND THEIR DISCREPANCIES*
"... Abstract. Quasirandom (also called low discrepancy) sequences are a deterministic alternative to random sequences for use in Monte Carlo methods, such as integration and particle simulations of transport processes. The error in uniformity for such a sequence ofN points in the sdimensional unit cub ..."
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Abstract. Quasirandom (also called low discrepancy) sequences are a deterministic alternative to random sequences for use in Monte Carlo methods, such as integration and particle simulations of transport processes. The error in uniformity for such a sequence ofN points in the sdimensional unit
Quasirandom graphs with given degree sequences
 RANDOM STRUCTURES AND ALGORITHMS
, 2008
"... It is now known that many properties of the objects in certain combinatorial structures are equivalent, in the sense that any object possessing any of the properties must of necessity possess them all. These properties, termed quasirandom, have been described for a variety of structures such as grap ..."
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Cited by 20 (1 self)
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It is now known that many properties of the objects in certain combinatorial structures are equivalent, in the sense that any object possessing any of the properties must of necessity possess them all. These properties, termed quasirandom, have been described for a variety of structures
QuasiRandom Sequences for Signal Sampling and Recovery
, 2010
"... HAL is a multidisciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte p ..."
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HAL is a multidisciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et a ̀ la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.
Modified Monte Carlo Methods Using QuasiRandom Sequences
 Lecture Notes in Statistics 106
, 1995
"... Computational experiments have shown that Monte Carlo methods using quasirandom sequences lose some of their effectiveness for integration problems in which the dimension is large or the integrand is not smooth. In this paper, two modified Monte Carlo methods are developed, which regain an enhanced ..."
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Cited by 18 (0 self)
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convergence rate. The standard rejection method involves discontinuities, corresponding to the decision to accept or reject. In place of this, a smoothed rejection method is formulated and found to be very effective when used with quasirandom sequences. Monte Carlo evaluation of FeynmanKac path integrals
100 FORMAL GROUP LAWS AND NONUNIFORM QUASIRANDOM SEQUENCES
, 2007
"... Abstract: In recent years, quasiMonte Carlo (QMC) integration methods have been successfully used in place of MonteCarlo methods in many applications. However, in practice, QMC integration is often applied to integrands on unbounded domains with nonuniform probability measures, integrals for whi ..."
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Cited by 1 (1 self)
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Abstract: In recent years, quasiMonte Carlo (QMC) integration methods have been successfully used in place of MonteCarlo methods in many applications. However, in practice, QMC integration is often applied to integrands on unbounded domains with nonuniform probability measures, integrals
Parallel Computation of Multivariate Normal Probabilities
"... We present methods for the computation of multivariate normal probabilities on parallel/ distributed systems. After a transformation of the initial integral, an approximation can be obtained using MonteCarlo or quasirandom methods. We propose a metaalgorithm for asynchronous sampling methods and d ..."
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Cited by 217 (9 self)
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and derive efficient parallel algorithms for the computation of MVN distribution functions, including a method based on randomized Korobov and Richtmyer sequences. Timing results of the implementations using the MPI parallel environment are given. 1 Introduction The computation of the multivariate normal
An Improved Method to Extract QuasiRandom Sequences from Generalized SemiRandom Sources
, 1999
"... this paper is to constr8z a quasirz0AC generrz using (A,#)SRSs. The following pr2 osition says that if agener823 outputs each element over ..."
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this paper is to constr8z a quasirz0AC generrz using (A,#)SRSs. The following pr2 osition says that if agener823 outputs each element over
Author manuscript, published in "SAMPTA'09, Marseille: France (2009)" QuasiRandom Sequences for Signal Sampling and Recovery
, 2010
"... The problem of reconstruction of bandlimited signals from sampled and noisy observations is studied. It is proposed to sample a signal at quasirandom points, that form a deterministic sequence with properties resembling a random variable being uniformly distributed. Such quasirandom points can be ..."
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The problem of reconstruction of bandlimited signals from sampled and noisy observations is studied. It is proposed to sample a signal at quasirandom points, that form a deterministic sequence with properties resembling a random variable being uniformly distributed. Such quasirandom points can
Monte Carlo and QuasiMonte Carlo methods
 ACTA NUMERICA
, 1998
"... Monte Carlo is one of the most versatile and widely used numerical methods. Its convergence rate, O(N ~ 1 ^ 2), is independent of dimension, which shows Monte Carlo to be very robust but also slow. This article presents an introduction to Monte Carlo methods for integration problems, including conve ..."
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Cited by 102 (3 self)
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convergence theory, sampling methods and variance reduction techniques. Accelerated convergence for Monte Carlo quadrature is attained using quasirandom (also called lowdiscrepancy) sequences, which are a deterministic alternative to random or pseudorandom sequences. The points in a quasirandom sequence
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