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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 51–75 of 256 papers

TitleStatusHype
Approaching human 3D shape perception with neurally mappable models—0
AI-Powered Prediction of Nanoparticle Pharmacokinetics: A Multi-View Learning Approach—0
Advanced Assessment of Stroke in Retinal Fundus Imaging with Deep Multi-view Learning—0
DualHGNN: A Dual Hypergraph Neural Network for Semi-Supervised Node Classification based on Multi-View Learning and Density Awareness—0
ARMOURED: Adversarially Robust MOdels using Unlabeled data by REgularizing Diversity—0
Adaptive Multi-View ICA: Estimation of noise levels for optimal inference—0
Deep Code Search with Naming-Agnostic Contrastive Multi-View Learning—0
Alternately Optimized Graph Neural Networks—0
Bayesian Sparse Factor Analysis with Kernelized Observations—0
Deep Incomplete Multi-view Learning via Cyclic Permutation of VAEs—0
A Multi-view Context-aware Approach to Android Malware Detection and Malicious Code Localization—0
Deep Multi-View Learning for Tire Recommendation—0
Bayesian multi-tensor factorization—0
An introduction to R package `mvs`—0
A Multi-view Perspective of Self-supervised Learning—0
Auto-weighted Multi-view Feature Selection with Graph Optimization—0
A Deep Network for Explainable Prediction of Non-Imaging Phenotypes using Anatomical Multi-View Data—0
Active Regression with Adaptive Huber Loss—0
Auto-Encoder based Co-Training Multi-View Representation Learning—0
A Unifying Framework in Vector-valued Reproducing Kernel Hilbert Spaces for Manifold Regularization and Co-Regularized Multi-view Learning—0
A Multi-View Learning Approach to Enhance Automatic 12-Lead ECG Diagnosis Performance—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
A Multi-View Joint Learning Framework for Embedding Clinical Codes and Text Using Graph Neural Networks—0
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