Interpolation Consistency Training for Semi-Supervised Learning

Vikas Verma

Abstract:

We introduce Interpolation Consistency Training (ICT), a simple and computation
efficient algorithm for training Deep Neural Networks in the semi-supervised
learning paradigm. ICT encourages the prediction at an interpolation of unlabeled
points to be consistent with the interpolation of the predictions at those points. In
classification problems, ICT moves the decision boundary to low-density regions
of the data distribution. Our experiments show that ICT achieves state-of-theart
performance when applied to standard neural network architectures on the
CIFAR-10 and SVHN benchmark datasets.