Efficient implementation of Semi-Stochastic Gradient Descent algorithm (S2GD) for training logistic regression (L2-regularized).
The S2GD algorithm enjoys linear convergence (faster than SGD), and comes without the need of tuning parameters like stepsize (choice explained in paper).
The code is in C++, called from MATLAB. The code is well commented, and should be easily adjusted for different applications.
The package also contains implementation of SGD and SAG.
First time usage:
>> mexAll % compiles the .cpp files
- Changes to previous version:
Initial Announcement on mloss.org.
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