More concretely, for each x x x ∈ D pool rnd and its correct label y y y , the underlying model m φ φ φt is re-trained to get is a small subset of the current large pool of unlabeled data.
the expert action is then computed as: our algorithmic expert tries a subset of actions to roll-out one step from the current state, in order to efficiently compute a reasonable action.