Deep Topic Models for Multi-label Learning

We present a probabilistic framework for multi-label learning based on a deep generative model for the binary label vector associated with each observation. Our generative model learns deep multi-layer latent embeddings of the binary label vector, which are conditioned on the input features of the observation. The model also has an intere...More