9 papers with code • 2 benchmarks • 1 datasets
Adversarial training provides a means of regularizing supervised learning algorithms while virtual adversarial training is able to extend supervised learning algorithms to the semi-supervised setting.
Ranked #13 on Sentiment Analysis on IMDb
This paper presents MixText, a semi-supervised learning method for text classification, which uses our newly designed data augmentation method called TMix.
Normalizing flows transform a latent distribution through an invertible neural network for a flexible and pleasingly simple approach to generative modelling, while preserving an exact likelihood.
In this paper, we study bidirectional LSTM network for the task of text classification using both supervised and semi-supervised approaches.
Ranked #3 on Text Classification on AG News
We present semi-supervised models with data augmentation (SMDA), a semi-supervised text classification system to classify interactive affective responses.