Smooth Neighbors on Teacher Graphs for Semi-Supervised Learning
Smooth Neighbors on Teacher Graphs for Semi-Supervised Learning
The recently proposed self-ensembling methods have achieved promising results in deep semi-supervised learning, which penalize inconsistent predictions of unlabeled data under different perturbations. However, they only consider adding perturbations to each single data point, while ignoring the connections between data samples. In this paper, we propose a novel method, called …