Challenging the Semi-Supervised VAE Framework for Text Classification

Ghazi Felhi, Joseph Le Roux, Djamé Seddah

Semi-Supervised Variational Autoencoders (SSVAEs) are widely used models for data efficient learning. In this paper, we question the adequacy of the standard design of sequence SSV…