Calculation of the gradient of a function in BFGS Quasi-Newton Algorithm
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I have a function that I want to minimize using the BFGS Quasi-Newton algorithm.
If .
are given.
Also, A is given, B is not given, and C is a function of B only.
If I want to calculate to the gradient of the function (). Should I calculate it with respect to all variables or with respect to B only?
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Accepted Answer
Matt J
on 27 May 2020
With respect to all the variables that are unknown.
4 Comments
Matt J
on 28 May 2020
Edited: Matt J
on 29 May 2020
It can be true. Or you can treat B and C as separate unknowns subject to an equality constraint,
C-g(B)=0
where g() is the function relating C to B. But it may make the optimization algorithm slower if it has to deal with additional variables and constraints.
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