Probabilistic Linear Discriminant Analysis Based on L 1 -Norm and Its Bayesian Variational Inference

Probabilistic linear discriminant analysis (PLDA) is a very effective feature extraction approach and has obtained extensive and successful applications in supervised learning tasks. It employs the squared $L_{2}$ -norm to measure the model errors, which assumes a Gaussian noise distribution implicitly. However, the noise in r...