What flavor of SVM are you trying to support? LSSVM doesn't need a bound constraint, but most other formulations do. There have been ideas for bound-constrained CG, though bounded LBFGS is more common. I think code for Nystrom approximations or kernel mappings would be more useful.
On Fri, Jun 27, 2014 at 5:42 PM, Debasish Das <debasish.da...@gmail.com> wrote: > Thanks David...Let me try it...I am keen to see the results first and later > will look into runtime optimizations... > > Deb > > > > > > On Fri, Jun 27, 2014 at 3:12 PM, David Hall <d...@cs.berkeley.edu> wrote: > > > I have no ideas on benchmarks, but breeze has a CG solver: > > > > > https://github.com/scalanlp/breeze/tree/master/math/src/main/scala/breeze/optimize/linear/ConjugateGradient.scala > > > > > > > https://github.com/scalanlp/breeze/blob/e2adad3b885736baf890b306806a56abc77a3ed3/math/src/test/scala/breeze/optimize/linear/ConjugateGradientTest.scala > > > > It's based on the code from TRON, and so I think it's more targeted for > > norm-constrained solutions of the CG problem. > > > > > > > > > > > > > > > > > > On Fri, Jun 27, 2014 at 5:54 PM, Debasish Das <debasish.da...@gmail.com> > > wrote: > > > > > Hi, > > > > > > I am looking for an efficient linear CG to be put inside the Quadratic > > > Minimization algorithms we added for Spark mllib. > > > > > > With a good linear CG, we should be able to solve kernel SVMs with this > > > solver in mllib... > > > > > > I use direct solves right now using cholesky decomposition which has > > higher > > > complexity as matrix sizes become large... > > > > > > I found out some jblas example code: > > > > > > https://github.com/mikiobraun/jblas-examples/blob/master/src/CG.java > > > > > > I was wondering if mllib developers have any experience using this > solver > > > and if this is better than apache commons linear CG ? > > > > > > Thanks. > > > Deb > > > > > >
