Add to ORKGThe L_2-discrepancy is a quantitative measure of precision for multivariate quadrature rules. It can be computed explicitly. Previously known algorithms needed O(m"2) operations, where m is the number of nodes. In this paper we present algorithms which require O(m(log m)"d) operations. (orig.)Available from TIB Hannover: RN 7281(267) / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekSIGLEDEGerman
In classical multivariate quadrature with product rules it is natural to select an appropriate one-d...
AbstractBirkholl quadrature formulae (q.f.), which have algebraic degree of precision (ADP) greater ...
The classical algorithm for multiple-precision division normalizes digits during each step and s...
The \(L_2\)-discrepancy is a quantitative measure of precision for multivariate quadrature rules. It...
AbstractIn recent years, Smolyak quadrature rules (also called quadratures on hyperbolic cross point...
AbstractIn recent years, Smolyak quadrature rules (also called quadratures on hyperbolic cross point...
In this book chapter we survey known approaches and algorithms to compute discrepancy measures of po...
AbstractThe L2-discrepancy measures the irregularity of the distribution of a finite point set. In t...
Linear discrepancy is a variant of discrepancy that measures how well we can round vectors w in $[0,...
Linear discrepancy is a variant of discrepancy that measures how well we can round vectors w in $[0,...
A notion of discrepancy is introduced, which represents the integration error on spaces of r-smooth ...
The L 2 -discrepancy for anchored axis-parallel boxes has been used in several recent computational ...
AbstractTheL2-discrepancy for anchored axis-parallel boxes has been used in several recent computati...
AbstractBirkholl quadrature formulae (q.f.), which have algebraic degree of precision (ADP) greater ...
We study the problem of rounding a real-valued matrix into an integer-valued matrix to minimize an L...
In classical multivariate quadrature with product rules it is natural to select an appropriate one-d...
AbstractBirkholl quadrature formulae (q.f.), which have algebraic degree of precision (ADP) greater ...
The classical algorithm for multiple-precision division normalizes digits during each step and s...
The \(L_2\)-discrepancy is a quantitative measure of precision for multivariate quadrature rules. It...
AbstractIn recent years, Smolyak quadrature rules (also called quadratures on hyperbolic cross point...
AbstractIn recent years, Smolyak quadrature rules (also called quadratures on hyperbolic cross point...
In this book chapter we survey known approaches and algorithms to compute discrepancy measures of po...
AbstractThe L2-discrepancy measures the irregularity of the distribution of a finite point set. In t...
Linear discrepancy is a variant of discrepancy that measures how well we can round vectors w in $[0,...
Linear discrepancy is a variant of discrepancy that measures how well we can round vectors w in $[0,...
A notion of discrepancy is introduced, which represents the integration error on spaces of r-smooth ...
The L 2 -discrepancy for anchored axis-parallel boxes has been used in several recent computational ...
AbstractTheL2-discrepancy for anchored axis-parallel boxes has been used in several recent computati...
AbstractBirkholl quadrature formulae (q.f.), which have algebraic degree of precision (ADP) greater ...
We study the problem of rounding a real-valued matrix into an integer-valued matrix to minimize an L...
In classical multivariate quadrature with product rules it is natural to select an appropriate one-d...
AbstractBirkholl quadrature formulae (q.f.), which have algebraic degree of precision (ADP) greater ...
The classical algorithm for multiple-precision division normalizes digits during each step and s...