LibSGDQN 1.1

antoine bordes, leon bottou — Thu, 02 Jul 2009 15:02:44 -0000

LibSGDQN proposes an implementation of SGD-QN, a carefully designed quasi-Newton stochastic gradient descent solver for linear SVMs.

The SGD-QN algorithm is a stochastic gradient descent algorithm that makes careful use of second order information and splits the parameter update into independently scheduled components. Thanks to this design, SGD-QN iterates nearly as fast as a first order stochastic gradient descent but requires less iterations to achieve the same accuracy.

This algorithm is extensively described in the paper: "SGD-QN: Careful Quasi-Newton Stochastic Gradient Descent" by A. Bordes, L. Bottou and P. Gallinari published in Journal of Machine Learning Research: Special Topic on Large Scale Learning (2009).

Along with SGD-QN, this library proposes the implementation of two other online solvers for linear SVMs (also discussed in the JMLR paper). A script to re-run the experiments of this paper is also provided.

Comment by looya.B on 2009-07-08 07:41

looya.B — Wed, 08 Jul 2009 07:41:42 -0000

sorry, there is nothing in my download files.

what happened?

Comment by Antoine Bordes on 2009-07-08 08:27

Antoine Bordes — Wed, 08 Jul 2009 08:27:28 -0000

Did you run the 'get_datat.sh' script in the 'data/' directory? This downloads the datafiles (and might take quite a while ... ) It's working ok for me.

mloss.org LibSGDQN

LibSGDQN 1.1

Comment by looya.B on 2009-07-08 07:41

Comment by Antoine Bordes on 2009-07-08 08:27