The files here demonstrate the algorithm in our ICML 2014 paper Discriminative Features via Generalized Eigenvectors
For the purposes of this demo, we use the calibrated least squares algorithm from our least squares paper as the optimizer. A version of this algorithm is included in this repository. You can also check the least squares repository for other algorithms (that work as well or better with the features here)
gemdriver does the following on the mnist digit dataset
- extracts GEM features and fits a multiclass classifier
- extracts two layers of GEM features and fits a multiclass classifier