Argonne National Laboratory

Obtaining Quadratic Models of Noisy Functions

TitleObtaining Quadratic Models of Noisy Functions
Publication TypeJournal Article
Year of Publication2011
AuthorsKannan, A, Wild, SM
Date Published11/2011
Other NumbersANL/MCS-P1975-1111

When derivatives of a nonlinear objective function are unavailable, many derivative-free optimization algorithms rely on interpolation-based models of the function. But what if the function values are contaminated by noise, as in most of the simulation-based problems typically encountered in this area? We propose to obtain linear and quadratic models by using knowledge of the level of noise in a function. We develop an efficient algorithm for obtaining the model coefficients, and we analyze the properties of the corresponding quadratic program.