1989 Reports
Average Case Complexity of Multivariate Integration
We study the average case complexity of multivariate integration for the class of continuous functions of d variables equipped with the classical Wiener sheet measure. To derive the average case complexity one needs to obtain optimal sample points. We prove that optimal design is closely related to discrepancy theory which has been extensively studied for many years. This relation enables us to show that optimal sample points can be derived from Hammersley points. Extending the result of Roth and using the recent result of Wasilkowski, we conclude that the average case complexity is θ(ε-1(lnε-1)(d-1)/2)
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- cucs-464-89.pdf application/pdf 322 KB Download File
More About This Work
- Academic Units
- Computer Science
- Publisher
- Department of Computer Science, Columbia University
- Series
- Columbia University Computer Science Technical Reports, CUCS-464-89
- Published Here
- December 23, 2011