JSGD: SGD for large-scale classification
This a Stochastic Gradient Descent algorithm used to train linear
multiclass classifiers. It is biased towards large classification
problems (many classes, many examples, high dimensional data).
The SGD implementation corresponds to the articles:
The latest source is available here:
Previous (stable) version:
The Package includes:
- A readable Matlab implementation of the SGD method based on the paper;
- A C implementation of SGD, intended to be fast;
- Matlab and Python interfaces to the C package;
- Test scripts;
- An optimization method that finds the best parameters for
the SGD by cross-validation.
Documentation is in the README file of the package.
Here are a few associated datafiles. They all contain descriptor in .fvecs format, computed on Imagenet subsets.
Feedback is welcome to
- mattis (dot) paulin (at) inria (dot) fr
Last modified: June 19, 2013.