Deep Learning, Artificial Intelligence, Semi Supervised Learning, Image Classification, Data Augmentation.
each training step, for each image two transformations are sampled uniformly at random. A modified set of bin weights ^m is produced where ^mi = mi if mi>0.8 and ^mi=0 otherwise, and magnitude bins are sampled from Categorical(Normalize(^m)). The resulting transformations are applied to a labeled