There's also the excellent uncertainties package (http://pypi.python.org/pypi/uncertainties/) for implicit automatic differentiation.
On Mon, Oct 1, 2012 at 7:44 AM, Joseph Turian <[email protected]> wrote: > Can anyone compare Theano and openopt for automatic differentiation? > > On Fri, Sep 28, 2012 at 2:36 PM, Dmitrey <[email protected]> wrote: >> Hi all, >> nice to hear about another one OpenOpt application. >> >>> For small non linear problems having an exact SVM/SVR solver >>> (not approximated) is very useful IMHO. >> >> I'm not sure what does this mean "For small non linear problems having >> an exact SVM/SVR solver (not approximated) is very useful IMHO" >> >> ralg cannot search solution with required tolerance, and thus is approximate >> solver (maybe in ML "exact/approximate" have a certain meaning? I'm not aware >> though). That "ftol" in the code is only a stopping criterion. >> For large problems (e.g. 10^4,10^5 variables) using ralg is impossible (it >> stores dense matrix of shape nVars x nVars in RAM), but you could try the >> constrained solvers like http://openopt.org/IPOPT, >> http://openopt.org/ALGENCAN >> or http://openopt.org/gsubg; latter can handle fTol - required tolerance >> abs(f-f*)<fTol, see also my post "routine for linear least norms problems" >> http://forum.openopt.org/viewtopic.php?id=598 . All these solvers are >> installed >> and thus can be tried in oursage server (http://sage.openopt.org), although, >> it >> has quite low equipment (1 GB RAM, 2 GHz processor). >> >>>Please put on sunglasses before opening the openopt webpage. >> >> OpenOpt website will be moved to new engine as soon as we will got >> possibilities >> to make it done. >> >> FYI in 2012, after 41 years since initial ralg article in 1971, >> N.G.Zhurbenko, >> co-author of r-algorithm (http://openopt.org/NikolayZhurbenko) seems to have >> invented major enhancement for r-algorithm, but I haven't possibilities to >> code >> it into my implementation of the solver (http://openopt.org/ralg) right now, >> mb >> it will be done several months later. >> >> ------------ >> Regards, D. >> http://openopt.org/Dmitrey >> >> >> ------------------------------------------------------------------------------ >> Got visibility? >> Most devs has no idea what their production app looks like. >> Find out how fast your code is with AppDynamics Lite. >> http://ad.doubleclick.net/clk;262219671;13503038;y? >> http://info.appdynamics.com/FreeJavaPerformanceDownload.html >> _______________________________________________ >> Scikit-learn-general mailing list >> [email protected] >> https://lists.sourceforge.net/lists/listinfo/scikit-learn-general > > > > -- > Joseph Turian, Ph.D. | President, MetaOptimize > "Optimize Profits. Optimize Engagement." > http://metaoptimize.com > 855-ALL-DATA > > The web's most active forum for data scientists: http://metaoptimize.com/qa/ > > ------------------------------------------------------------------------------ > Got visibility? > Most devs has no idea what their production app looks like. > Find out how fast your code is with AppDynamics Lite. > http://ad.doubleclick.net/clk;262219671;13503038;y? > http://info.appdynamics.com/FreeJavaPerformanceDownload.html > _______________________________________________ > Scikit-learn-general mailing list > [email protected] > https://lists.sourceforge.net/lists/listinfo/scikit-learn-general ------------------------------------------------------------------------------ Got visibility? Most devs has no idea what their production app looks like. Find out how fast your code is with AppDynamics Lite. http://ad.doubleclick.net/clk;262219671;13503038;y? http://info.appdynamics.com/FreeJavaPerformanceDownload.html _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
