The SGD package contains a stochastic gradient implementation of linear SVMs and linear CRFs. It demonstrate that a simple stochastic gradient descent is very competitive algorithm for such tasks. For instance, the SVMSGD program digests the RCV1 database in slightly more than one second, and the CRFSGD code runs close to ten times faster then the CRF++ Limited Storage BFGS optimizer.
- Changes to previous version:
Initial Announcement on mloss.org.
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