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 >
