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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
Siamese DETRCode1
Reliable Representations Learning for Incomplete Multi-View Partial Multi-Label Classification—0
Deep Double Incomplete Multi-view Multi-label Learning with Incomplete Labels and Missing ViewsCode0
MetaViewer: Towards A Unified Multi-View Representation—0
Deep Transfer Tensor Factorization for Multi-View Learning—0
ConsRec: Learning Consensus Behind Interactions for Group RecommendationCode1
A Multi-View Joint Learning Framework for Embedding Clinical Codes and Text Using Graph Neural Networks—0
Heterogeneous Domain Adaptation and Equipment Matching: DANN-based Alignment with Cyclic Supervision (DBACS)—0
MHCN: A Hyperbolic Neural Network Model for Multi-view Hierarchical Clustering—0
A Clustering-guided Contrastive Fusion for Multi-view Representation LearningCode1
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