[amitness]

Nope,because of the way it works. So in the beginning when the model is being trained on the labeled data, it will make many mistakes. So it's confidence for either cat or dog will be low. Hence, in that case unlabeled data are not used at all.

As training progresses, the model will become better at labeled data. And so it can start predicting with high confidence on unlabeled images that are trivial/similar-looking/same distribution with labeled data. So, gradually unlabeled images get started being used as part of training. As training progresses, more and more unlabeled data are added.

The mathematics of the combined loss function and curriculum learning part talks about this.