On Fri, Sep 28, 2012 at 3:48 PM, Mathieu Blondel <[email protected]>wrote:
> # If you do subgradient descent, you can use non-smooth losses. In the
> paper I mentioned, the author is using Newton's method, which is why he's
> using differentiable losses.
>
Exactly, In fact ralg supports non smooth functions [1] via (automatically
calcualted)
sub gradient information and I found it extremely robust and fast.
At least for my problems...
[1] http://en.wikipedia.org/wiki/Naum_Z._Shor#r-algorithm
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