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Re: algorithm for fminunc
From: |
Jose |
Subject: |
Re: algorithm for fminunc |
Date: |
Mon, 21 Jan 2013 16:43:40 +0200 |
User-agent: |
Mozilla/5.0 (X11; Linux x86_64; rv:17.0) Gecko/20130106 Thunderbird/17.0.2 |
On 01/18/2013 07:13 PM, Jordi Gutiérrez Hermoso wrote:
I don't find the code too difficult to read. Upon further inspection,
it is precisely damped BFSG with a dogleg trust region method. This is
a fairly standard method. For example, you can read about it in
Nocedal & Wright, section 18.4 (procedure 18.2). This is even using
the same notation as the Octave source code. The dogleg line search is
in op. cit. section 4.1.
Thanks for the reference, I found it.
No other algorithm seems to be implemented here. Are you planning to
add more algorithms? Does Matlab have an interface for choosing the
algorithm? There could be improvements here.
According to
http://www.mathworks.se/help/optim/ug/fminunc.html
fminunc from Matlab can use two algorithms, one for large-scale
optimization and another for medium-scale. BGFS is used in the second
one. For the first one it uses an "interior-reflective Newton method" by
Coleman et.al. The documentation provides the references to the
appropriate articles.
I am not planning on implementing any new method, at least for now.
Once I'm more certain that Nocedal & Wright is
the appropriate reference, and it would help if you could confirm
this, I will add the reference to the comments.
I'd love to help on this, but I am not an expert in optimization and it
would take me too long at this moment to understand well what is going
on under the hood.
But what about asking the original author? The code was written by
Jaroslav Hajek, I hope he is reading this thread :)
Jose