Deep Topic Models for Multi-label Learning

international conference on artificial intelligence and statistics, 2019.

Cited by: 1|Views12

Abstract:

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

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