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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 71–80 of 256 papers

TitleStatusHype
A Unifying Framework in Vector-valued Reproducing Kernel Hilbert Spaces for Manifold Regularization and Co-Regularized Multi-view Learning—0
A Comparison of Multi-View Learning Strategies for Satellite Image-Based Real Estate Appraisal—0
Diverse and Consistent Multi-view Networks for Semi-supervised Regression—0
A unified framework based on graph consensus term for multi-view learning—0
Dissimilarity-based representation for radiomics applications—0
DualHGNN: A Dual Hypergraph Neural Network for Semi-Supervised Node Classification based on Multi-View Learning and Density Awareness—0
Auto-Encoder based Co-Training Multi-View Representation Learning—0
A Multi-View Joint Learning Framework for Embedding Clinical Codes and Text Using Graph Neural Networks—0
Auto-weighted Multi-view Feature Selection with Graph Optimization—0
A Deep Multi-View Learning Framework for City Event Extraction from Twitter Data Streams—0
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