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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 126–150 of 256 papers

TitleStatusHype
Self-attention Multi-view Representation Learning with Diversity-promoting Complementarity—0
A Novel TSK Fuzzy System Incorporating Multi-view Collaborative Transfer Learning for Personalized Epileptic EEG Detection—0
Saliency-based Multi-View Mixed Language Training for Zero-shot Cross-lingual Classification—0
TSK Fuzzy System Towards Few Labeled Incomplete Multi-View Data Classification—0
Diverse and Consistent Multi-view Networks for Semi-supervised Regression—0
Information Theory-Guided Heuristic Progressive Multi-View Coding—0
Locality Relationship Constrained Multi-view Clustering Framework—0
A unified framework based on graph consensus term for multi-view learning—0
ASM2TV: An Adaptive Semi-Supervised Multi-Task Multi-View Learning Framework for Human Activity RecognitionCode0
A Comparison of Multi-View Learning Strategies for Satellite Image-Based Real Estate Appraisal—0
Few-shot Partial Multi-view Learning—0
Weak Multi-View Supervision for Surface Mapping Estimation—0
Federated Multi-View Learning for Private Medical Data Integration and Analysis—0
Text-to-Text Multi-view Learning for Passage Re-ranking—0
Auto-weighted Multi-view Feature Selection with Graph Optimization—0
X-view: Non-egocentric Multi-View 3D Object Detector—0
Multi-view Audio and Music Classification—0
Self-Supervised Multi-View Learning via Auto-Encoding 3D Transformations—0
Adaptive Multi-View ICA: Estimation of noise levels for optimal inference—0
Trace Ratio Optimization with an Application to Multi-view Learning—0
ARMOURED: Adversarially Robust MOdels using Unlabeled data by REgularizing Diversity—0
Multi-view Temporal Alignment for Non-parallel Articulatory-to-Acoustic Speech SynthesisCode0
A Multi-View Dynamic Fusion Framework: How to Improve the Multimodal Brain Tumor Segmentation from Multi-Views?—0
InSRL: A Multi-view Learning Framework Fusing Multiple Information Sources for Distantly-supervised Relation Extraction—0
Partially Shared Semi-supervised Deep Matrix Factorization with Multi-view DataCode0
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