2017
Scalable Generative Models for Multi-label Learning with Missing Labels
ICML 2017poster
We present a scalable, generative framework for multi-label learning with missing labels. Our framework consists of a latent factor model for the binary label matrix, which is coupled with an exposure model to account for label missingness (i.e., whether a zero in the label matrix is indeed a zero o…