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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

Showing 1120 of 256 papers

TitleStatusHype
Siamese DETRCode1
ConsRec: Learning Consensus Behind Interactions for Group RecommendationCode1
A Clustering-guided Contrastive Fusion for Multi-view Representation LearningCode1
Common Practices and Taxonomy in Deep Multi-view Fusion for Remote Sensing ApplicationsCode1
Heterogeneous Graph Contrastive Multi-view LearningCode1
Localized Sparse Incomplete Multi-view ClusteringCode1
Variational Distillation for Multi-View LearningCode1
Shared Independent Component Analysis for Multi-Subject NeuroimagingCode1
Duo-SegNet: Adversarial Dual-Views for Semi-Supervised Medical Image SegmentationCode1
Farewell to Mutual Information: Variational Distillation for Cross-Modal Person Re-IdentificationCode1
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