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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 101–150 of 256 papers

TitleStatusHype
Asymmetric Proxy Loss for Multi-View Acoustic Word Embeddings—0
Deep Multi-View Learning for Tire Recommendation—0
Variational Interpretable Learning from Multi-view Data—0
Higher Order Correlation Analysis for Multi-View Learning—0
Multi-view learning with privileged weighted twin support vector machine—0
Exploring the Value of Multi-View Learning for Session-Aware Query Representation—0
Uncertainty-Aware Multi-View Representation Learning—0
Multi-View representation learning in Multi-Task Scene—0
Auto-Encoder based Co-Training Multi-View Representation Learning—0
Multi-View Non-negative Matrix Factorization Discriminant Learning via Cross Entropy Loss—0
Multi-view Data Classification with a Label-driven Auto-weighted Strategy—0
Self-attention Multi-view Representation Learning with Diversity-promoting Complementarity—0
Multi-view Subspace Adaptive Learning via Autoencoder and Attention—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
Shared Independent Component Analysis for Multi-Subject NeuroimagingCode1
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
Duo-SegNet: Adversarial Dual-Views for Semi-Supervised Medical Image SegmentationCode1
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
Farewell to Mutual Information: Variational Distillation for Cross-Modal Person Re-IdentificationCode1
X-view: Non-egocentric Multi-View 3D Object Detector—0
COMPLETER: Incomplete Multi-view Clustering via Contrastive PredictionCode1
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
Trusted Multi-View ClassificationCode1
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
Co-mining: Self-Supervised Learning for Sparsely Annotated Object DetectionCode1
Partially Shared Semi-supervised Deep Matrix Factorization with Multi-view DataCode0
Uncorrelated Semi-paired Subspace Learning—0
Deep Partial Multi-View Learning—0
Layer-Wise Multi-View Learning for Neural Machine Translation—0
Generative View-Correlation Adaptation for Semi-Supervised Multi-View Learning—0
Random Forest for Dissimilarity-based Multi-view Learning—0
Embedded Deep Bilinear Interactive Information and Selective Fusion for Multi-view Learning—0
Multi-view Orthonormalized Partial Least Squares: Regularizations and Deep Extensions—0
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