Hey Josef, If the problem you are dealing with is some kind of least square problem, you might find this paper helpful: Federico
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On Sat, Oct 19, 2013 at 5:09 PM, federico vaggi
<[hidden email]> wrote: > Hey Josef, > > If the problem you are dealing with is some kind of least square problem, > you might find this paper helpful: > > http://arxiv.org/abs/1201.5885 Thanks for the link. My problem has a quadratic form but it cannot be rewritten as a least squares problem, at least not in it's general form. That's the reason I'm using the general optimizers, mainly fmin and fmin_bfgs. Josef > > Federico > >> >> Message: 1 >> Date: Fri, 18 Oct 2013 22:16:28 -0400 >> From: [hidden email] >> Subject: [SciPy-User] optimization with ill conditioned Hessian >> To: SciPy Users List <[hidden email]> >> Message-ID: >> >> <[hidden email]> >> Content-Type: text/plain; charset=ISO-8859-1 >> >> Does scipy have another optimizer besides fmin (Nelder-Mead) that is >> robust to near-singular, high condition number Hessian? >> >> fmin_bfgs goes into neverland, values become huge until I get some >> nans in my calculations. >> >> What would be nice is an optimizer that uses derivatives, but >> regularizes, forces Hessian or equivalent to be positive definite. >> >> >> Background >> I'm trying to replicate a textbook example that has data and matrix >> inverses that are "not nice". fmin (Nelder-Mead) is getting pretty >> close to the Stata numbers. However fmin_bfgs has been my preferred >> default optimizer for some time. >> >> Aside: >> It looks like it's a good test case to make my linear algebra more robust. >> np.linalg.pinv(x.T.dot(x)) doesn't seem to be robust enough for this case. >> And no idea why a textbook would use an example like that. >> And no idea if Stata doesn't just make up the numbers. >> >> Thanks, >> >> Josef >> > > _______________________________________________ > SciPy-User mailing list > [hidden email] > http://mail.scipy.org/mailman/listinfo/scipy-user > SciPy-User mailing list [hidden email] http://mail.scipy.org/mailman/listinfo/scipy-user |
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