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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 141–150 of 256 papers

TitleStatusHype
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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