Variational inference framework for partial multi-view multi-label representation learning

doi:10.1016/j.patcog.2026.113742

Variational inference framework for partial multi-view multi-label representation learning

2026-04-16

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DOI：10.1016/j.patcog.2026.113742

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Abstract

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• Multi-view random dropping augmentation improves model generalization. • Learns joint representation by optimizing three mutual information terms. • The proposed framework explains the process for learning optimal shared information.

Keywords:

multi-view learning

variational inference

mutual information

representation learning

random dropping augmentation

Variational inference framework for partial multi-view multi-label representation learning

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