Since it is unlabeled at time t, we know that φ (t) x is the uniform distribution u: must also be the uniform distribution; otherwise example x would have been labeled in a previous iteration.
the value of H(x) = H(φ x ||π x ) at the beginning of iteration t is H 0 : After the training step, the value is H 1 : If π x remains unchanged in the training step, then the new distribution π , like the old one, is the uniform distribution, and the example remains unlabeled.