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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 2130 of 256 papers

TitleStatusHype
CPM-Nets: Cross Partial Multi-View NetworksCode1
ConsRec: Learning Consensus Behind Interactions for Group RecommendationCode1
A Clustering-guided Contrastive Fusion for Multi-view Representation LearningCode1
Robust Variational Contrastive Learning for Partially View-unaligned ClusteringCode1
Deep Tensor CCA for Multi-view LearningCode1
Deep Multi-View Learning via Task-Optimal CCACode1
Localized Sparse Incomplete Multi-view ClusteringCode1
Dual Contrastive Prediction for Incomplete Multi-view Representation LearningCode1
Duo-SegNet: Adversarial Dual-Views for Semi-Supervised Medical Image SegmentationCode1
Variational Distillation for Multi-View LearningCode1
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