A Novel Generative Embedding Constraint and its Application to Semi-Supervised Image Classification
A novel Method of Moments (MoM) based embedding constraint enables a generative Axis-Aligned Gaussian Mixture Model (AAGMM) final layer to learn the joint distribution of the latent space, improving outlier detection and reducing over-confidence in semi-supervised image classification.