[Top][All Lists]
[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]
[Help-gsl] Stochastic descent in multimin functions
From: |
James Bergstra |
Subject: |
[Help-gsl] Stochastic descent in multimin functions |
Date: |
Wed, 12 Jan 2005 18:00:45 -0500 |
User-agent: |
Mutt/1.4.1i |
Hi,
I was wondering if is safe / sane to provide a function for minimization
that uses a stochastic gradient estimate. My gradient estimation would
thus produce different estimates for the same point, depending on the
internal state of the 'function'. Aside from yeilding a noisy gradient,
would this interfere with the optimization? Would one optimization type
be more appropriate than another in this case? (eg: grad descent vs.
conjugate transpose vs ?)
James Bergstra
- [Help-gsl] Stochastic descent in multimin functions,
James Bergstra <=