Hyper-parameter selection ?

[debasmitdas]

It seems that the reverse validation (rv) approach (as mentioned in the paper) to hyper-parameter selection has not been carried out in the repository. So I wanted to ask some of the gory implementation details that you used for reporting in the paper -

1. For the rv procedure you retrain the neural network multiple times using different parameters and test on the validation splits and choose the hyperparameter with the best result. Once you find the best hyper-parameter, you retrain the neural network using all the data and report accuracy on test data. Correct me if you did not follow such a policy.

2)Also, reverse validating a neural network over a range of hyparameters followed by retraining using the best hyperparameters, takes time . So, did you use a parallel procedure to report such results.