Papers › A Deep Generative Model for Semi-Supervised Classification with Noisy Labels
A Deep Generative Model for Semi-Supervised Classification with Noisy Labels
Maxime Langevin, Edouard Mehlman, Jeffrey Regier, Romain Lopez, Michael. I. Jordan, Nir Yosef
Class labels are often imperfectly observed, due to mistakes and to genuine ambiguity among classes. We propose a new semi-supervised deep generative model that explicitly models noisy labels, called the Mislabeled VAE (M-VAE). The M-VAE can perform better than existing deep generative models which do not account for label noise. Additionally, the derivation of M-VAE gives new theoretical insights into the popular M1+M2 semi-supervised model.
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