Obtaining Quadratic Models of Noisy Functions
|Title||Obtaining Quadratic Models of Noisy Functions|
|Publication Type||Journal Article|
|Year of Publication||2011|
|Authors||Kannan, A, Wild, SM|
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.