Retrospective-approximation algorithms for the multidimensional stochastic root-finding problem

Abstract

The stochastic root-finding problem (SRFP) is that of solving a nonlinear system of equations using only a simulation that provides estimates of the functions at requested points. Equivalently, SRFPs seek locations where an unknown vector function attains a given target using only a simulation capable of providing estimates of the function. SRFPs find application in a wide variety of physical settings.

Document Details

Document Type
Pub Defense Publication
Publication Date
Mar 01, 2009
Source ID
10.1145/1502787.1502788

Entities

People

  • Bruce W. Schmeiser
  • Raghu Pasupathy

Organizations

  • Office of Naval Research
  • Purdue University
  • Virginia Tech

Tags

Fields of Study

  • Mathematics

Readers

  • Approximation Theory.
  • Computational Fluid Dynamics (CFD)
  • Operations Research