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MULTI-VIEW LEARNING

Multi-View Learning is a machine learning framework where data are represented by multiple distinct feature groups, and each feature group is referred to as a particular view.

Source: Dissimilarity-based representation for radiomics applications

Papers

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Showing 121–130 of 256 papers

TitleStatusHype
Multi-View representation learning in Multi-Task Scene—0
Auto-Encoder based Co-Training Multi-View Representation Learning—0
Multi-View Non-negative Matrix Factorization Discriminant Learning via Cross Entropy Loss—0
Multi-view Data Classification with a Label-driven Auto-weighted Strategy—0
Multi-view Subspace Adaptive Learning via Autoencoder and Attention—0
Self-attention Multi-view Representation Learning with Diversity-promoting Complementarity—0
A Novel TSK Fuzzy System Incorporating Multi-view Collaborative Transfer Learning for Personalized Epileptic EEG Detection—0
Saliency-based Multi-View Mixed Language Training for Zero-shot Cross-lingual Classification—0
TSK Fuzzy System Towards Few Labeled Incomplete Multi-View Data Classification—0
Diverse and Consistent Multi-view Networks for Semi-supervised Regression—0
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