-

 

 

 




Optimization Online





 

Estimating Derivatives of Noisy Simulations

Jorge Moré (more***at***mcs.anl.gov)
Stefan Wild (wild***at***mcs.anl.gov)

Abstract: We employ recent work on computational noise to obtain near-optimal finite difference estimates of the derivatives of a noisy function. Our analysis employs a stochastic model of the noise without assuming a specific form of distribution. We use this model to derive theoretical bounds for the errors in the difference estimates and obtain an easily computable difference parameter that is provably near-optimal. Numerical results closely resemble the theory and show that we obtain accurate derivative estimates even when the noisy function is deterministic.

Keywords: Computational Noise, Finite Difference Derivatives, Noisy Simulations

Category 1: Other Topics (Other )

Category 2: Nonlinear Optimization (Other )

Category 3: Optimization Software and Modeling Systems (Other )

Citation: To appear in ACM Transactions on Mathematical Software, Vol 38, No 3. Formerly: Argonne National Laboratory Mathematics and Computer Science Division Preprint ANL/MCS-P1785-0810.

Download: [PDF]

Entry Submitted: 11/02/2010
Entry Accepted: 11/02/2010
Entry Last Modified: 09/14/2011

Modify/Update this entry


  Visitors Authors More about us Links
  Subscribe, Unsubscribe
Digest Archive
Search, Browse the Repository

 

Submit
Update
Policies
Coordinator's Board
Classification Scheme
Credits
Give us feedback
Optimization Journals, Sites, Societies
Mathematical Optimization Society