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Auto-Encoder based Co-Training Multi-View Representation Learning
As we known, auto-encoder is a method of deep learning, which can learn the latent feature of raw data by reconstructing the input, and based on this, we propose a novel algorithm called Auto-encoder based Co-training Multi-View Learning (ACMVL), which utilizes both complementarity and consistency and finds a joint latent feature representation of multiple views.
Multi-view Subspace Adaptive Learning via Autoencoder and Attention
Multi-view learning can cover all features of data samples more comprehensively, so multi-view learning has attracted widespread attention.
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