Auto differentiation vs finite differences in optimization toolbox
조회 수: 1 (최근 30일)
이전 댓글 표시
Is there a situation where finite differences is faster than automatic differentiation when using the "solve" function call in the optimization toolbox?
I'm using the optimization toolbox to solve an optimization problem with a complex loss funcation and relatively few optimization variables. I'm noticing a substantial speed up when changing the value of "ObjectiveDerivative" from "auto" to "finite-differences."
Any clarification would be greatly appreciated!
댓글 수: 0
답변 (1개)
Alan Weiss
2021년 7월 11일
Yes, finite differences can be faster than AD. Typically, this occurs in situations like yours where the function or functions are complicated , and the resulting AD expressions are even more complex.
That said, sometimes you can help the solver by setting up your problem in a way that enables solve to operate efficiently. See Create Efficient Optimization Problems and, to a lesser extent for your problem, Separate Optimization Model from Data.
Alan Weiss
MATLAB mathematical toolbox documentation
댓글 수: 0
참고 항목
카테고리
Help Center 및 File Exchange에서 Problem-Based Optimization Setup에 대해 자세히 알아보기
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!