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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 26–50 of 256 papers

TitleStatusHype
Shared Independent Component Analysis for Multi-Subject NeuroimagingCode1
LUMA: A Benchmark Dataset for Learning from Uncertain and Multimodal DataCode1
Localized Sparse Incomplete Multi-view ClusteringCode1
Farewell to Mutual Information: Variational Distillation for Cross-Modal Person Re-IdentificationCode1
Dual Adversarial Domain AdaptationCode1
A Multi-view Context-aware Approach to Android Malware Detection and Malicious Code Localization—0
A Solution for Large Scale Nonlinear Regression with High Rank and Degree at Constant Memory Complexity via Latent Tensor Reconstruction—0
Adaptive incomplete multi-view learning via tensor graph completion—0
Alternately Optimized Graph Neural Networks—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
A Reliable and Interpretable Framework of Multi-view Learning for Liver Fibrosis Staging—0
Approaching human 3D shape perception with neurally mappable models—0
AI-Powered Prediction of Nanoparticle Pharmacokinetics: A Multi-View Learning Approach—0
A Novel TSK Fuzzy System Incorporating Multi-view Collaborative Transfer Learning for Personalized Epileptic EEG Detection—0
A Novel Random Forest Dissimilarity Measure for Multi-View Learning—0
A graph neural network-based multispectral-view learning model for diabetic macular ischemia detection from color fundus photographs—0
Deep Incomplete Multi-view Learning via Cyclic Permutation of VAEs—0
Classification of weak multi-view signals by sharing factors in a mixture of Bayesian group factor analyzers—0
Canonical Correlation Analysis with Implicit Distributions—0
A Nonparametric Multi-view Model for Estimating Cell Type-Specific Gene Regulatory Networks—0
Canonical Correlation Analysis (CCA) Based Multi-View Learning: An Overview—0
Community-preserving Graph Convolutions for Structural and Functional Joint Embedding of Brain Networks—0
Anomaly detecting and ranking of the cloud computing platform by multi-view learning—0
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