Wed May 20 15:48:47 CDT 2009
On 20-May-09, at 3:51 PM, Jason Rennie wrote:
> I'm planning to use this function to optimize a least squares
> objective. I
> noticed that the "norm" argument defaults to "inf" or max norm.
> Does this
> mean that (by default) the search is done in max-norm space rather
> L2/Euclidean norm space? Should I be worried about this setting?
No; the termination criterion is based on the norm of the gradient. By
default, it uses the infinity norm.
This simply means that by default, the search terminates when _every_
element of the returned gradient is less than gtol. This is a bit
easier to think about than figuring out a tolerance on the 2-norm of
the gradient vector, especially in very high dimensional spaces.
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