> I wonder if anyone might have recommendation on scala native implementation > of SVD.
Mahout has a scala implementation of an SVD variant called Stochastic SVD: https://svn.apache.org/viewvc/mahout/trunk/math-scala/src/main/scala/org/apache/mahout/math/scalabindings/SSVD.scala?view=markup Otherwise, all the major java math libraries (mahout math, jblas, commons-math) should provide an implementation that you can use in scala. --sebastian > C > > > > > On Thu, Jan 2, 2014 at 7:06 PM, Ameet Talwalkar > <[email protected]>wrote: > >> Hi Deb, >> >> Thanks for your email. We currently do not have a DSGD implementation in >> MLlib. Also, just to clarify, DSGD is not a variant of ALS, but rather a >> different algorithm for solving the same the same bi-convex objective >> function. >> >> It would be a good thing to do add, but to the best of my knowledge, no >> one is actively working on this right now. >> >> Also, as you mentioned, the ALS implementation in mllib is more >> robust/scalable than the one in spark.examples. >> >> -Ameet >> >> >> On Thu, Jan 2, 2014 at 3:16 PM, Debasish Das <[email protected]>wrote: >> >>> Hi, >>> >>> I am not noticing any DSGD implementation of ALS in Spark. >>> >>> There are two ALS implementations. >>> >>> org.apache.spark.examples.SparkALS does not run on large matrices and >>> seems more like a demo code. >>> >>> org.apache.spark.mllib.recommendation.ALS looks feels more robust version >>> and I am experimenting with it. >>> >>> References here are Jellyfish, Twitter's implementation of Jellyfish >>> called Scalafish, Google paper called Sparkler and similar idea put forward >>> by IBM paper by Gemulla et al. (large-scale matrix factorization with >>> distributed stochastic gradient descent) >>> >>> https://github.com/azymnis/scalafish >>> >>> Are there any plans of adding DSGD in Spark or there are any existing >>> JIRA ? >>> >>> Thanks. >>> Deb >>> >>> >> > >
