Credit: CAAI Artificial Intelligence Research, Tsinghua University Press
Meta-Semi, shown in figure 1, trains deep networks using pseudo-labeled samples whose gradient directions are similar to labeled samples. Algorithm 1 shows the Meta Semi pseudo code. The Meta-Semi algorithm outperforms state-of-the-art semi-supervised learning algorithms.