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arXiv AI By Yiyang Shen, Weiran Wang

No Data Wasted: A Semi-supervised Generative Model for Incomplete Multi-view Data Integration with Missing Labels

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The paper presents a semi‑supervised generative model for multi‑view learning that handles missing views and missing labels. It combines a likelihood‑based approach for unlabeled data with an information bottleneck (IB) framework for labeled data, incorporating modality‑specific information and cross‑view mutual information maximization to learn a shared latent space. Experiments show improved predictive and generative performance on complex datasets with limited labeled samples.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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