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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 171–180 of 256 papers

TitleStatusHype
Multi-Participant Multi-Class Vertical Federated Learning—0
Adaptive Similarity Embedding for Unsupervised Multi-View Feature Selection—0
Semi-supervised Classification using Attention-based Regularization on Coarse-resolution Data—0
Towards Disentangled Representations for Human Retargeting by Multi-view Learning—0
Potential Passenger Flow Prediction: A Novel Study for Urban Transportation Development—0
The Similarity-Consensus Regularized Multi-view Learning for Dimension Reduction—0
Variable Star Classification Using Multi-View Metric Learning—0
Community-preserving Graph Convolutions for Structural and Functional Joint Embedding of Brain Networks—0
Neural News Recommendation with Heterogeneous User Behavior—0
Partners in Crime: Multi-view Sequential Inference for Movie Understanding—0
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