No Data Wasted: A Semi-supervised Generative Model for Incomplete Multi-view Data Integration with Missing Labels
This work proposes a semi-supervised generative model that utilizes both labeled and unlabeled samples in a unified framework and maximizes the likelihood of unlabeled samples to learn a latent space shared with the IB on labeled data.
Yiyang Shen, Wei-Ran Wang
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