Hello Prof. Lin, Awesome news ! I am curious if you have any benchmarks comparing C++ MPI with Scala Spark liblinear implementations...
Is Spark Liblinear apache licensed or there are any specific restrictions on using it ? Except using native blas libraries (which each user has to manage by pulling in their best proprietary BLAS package), all Spark code is Apache licensed. Thanks. Deb On Sun, May 11, 2014 at 3:01 AM, DB Tsai <dbt...@stanford.edu> wrote: > Dear Prof. Lin, > > Interesting! We had an implementation of L-BFGS in Spark and already > merged in the upstream now. > > We read your paper comparing TRON and OWL-QN for logistic regression with > L1 (http://www.csie.ntu.edu.tw/~cjlin/papers/l1.pdf), but it seems that > it's not in the distributed setup. > > Will be very interesting to know the L2 logistic regression benchmark > result in Spark with your TRON optimizer and the L-BFGS optimizer against > different datasets (sparse, dense, and wide, etc). > > I'll try your TRON out soon. > > > Sincerely, > > DB Tsai > ------------------------------------------------------- > My Blog: https://www.dbtsai.com > LinkedIn: https://www.linkedin.com/in/dbtsai > > > On Sun, May 11, 2014 at 1:49 AM, Chieh-Yen <r01944...@csie.ntu.edu.tw>wrote: > >> Dear all, >> >> Recently we released a distributed extension of LIBLINEAR at >> >> http://www.csie.ntu.edu.tw/~cjlin/libsvmtools/distributed-liblinear/ >> >> Currently, TRON for logistic regression and L2-loss SVM is supported. >> We provided both MPI and Spark implementations. >> This is very preliminary so your comments are very welcome. >> >> Thanks, >> Chieh-Yen >> > >
