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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 151–200 of 256 papers

TitleStatusHype
Scalable Multi-view Clustering via Explicit Kernel Features Maps—0
scICML: Information-theoretic Co-clustering-based Multi-view Learning for the Integrative Analysis of Single-cell Multi-omics data—0
SE(3) Equivariant Ray Embeddings for Implicit Multi-View Depth Estimation—0
Self-attention Multi-view Representation Learning with Diversity-promoting Complementarity—0
Self-boosted Time-series Forecasting with Multi-task and Multi-view Learning—0
Self-Supervised Multi-View Learning via Auto-Encoding 3D Transformations—0
Semi-supervised Classification using Attention-based Regularization on Coarse-resolution Data—0
Semi-supervised Multi-sensor Classification via Consensus-based Multi-View Maximum Entropy Discrimination—0
Speech representation learning: Learning bidirectional encoders with single-view, multi-view, and multi-task methods—0
Stacked Penalized Logistic Regression for Selecting Views in Multi-View Learning—0
Steinmetz Neural Networks for Complex-Valued Data—0
ST-MVL: Filling Missing Values in Geo-Sensory Time Series Data—0
Streaming View Learning—0
Text-to-Text Multi-view Learning for Passage Re-ranking—0
Texture and Structure Two-view Classification of Images—0
The Similarity-Consensus Regularized Multi-view Learning for Dimension Reduction—0
Towards Disentangled Representations for Human Retargeting by Multi-view Learning—0
Towards the Generalization of Multi-view Learning: An Information-theoretical Analysis—0
Trace Ratio Optimization with an Application to Multi-view Learning—0
TSK Fuzzy System Towards Few Labeled Incomplete Multi-View Data Classification—0
Uncertainty-Aware Multi-View Representation Learning—0
Uncertainty Quantification via Hölder Divergence for Multi-View Representation Learning—0
Uncertainty-Weighted Mutual Distillation for Multi-View Fusion—0
Uncorrelated Semi-paired Subspace Learning—0
Variable Star Classification Using Multi-View Metric Learning—0
Variational Inference for Deep Probabilistic Canonical Correlation Analysis—0
Variational Interpretable Learning from Multi-view Data—0
Variational recurrent models for representation learning—0
Visual-Texual Emotion Analysis with Deep Coupled Video and Danmu Neural Networks—0
Weak Multi-View Supervision for Surface Mapping Estimation—0
X-view: Non-egocentric Multi-View 3D Object Detector—0
A Comparison of Multi-View Learning Strategies for Satellite Image-Based Real Estate Appraisal—0
Active Regression with Adaptive Huber Loss—0
Adaptive incomplete multi-view learning via tensor graph completion—0
Adaptive Multi-View ICA: Estimation of noise levels for optimal inference—0
Adaptive Similarity Embedding for Unsupervised Multi-View Feature Selection—0
A Deep Multi-View Learning Framework for City Event Extraction from Twitter Data Streams—0
A Deep Network for Explainable Prediction of Non-Imaging Phenotypes using Anatomical Multi-View Data—0
Advanced Assessment of Stroke in Retinal Fundus Imaging with Deep Multi-view Learning—0
A graph neural network-based multispectral-view learning model for diabetic macular ischemia detection from color fundus photographs—0
AI-Powered Prediction of Nanoparticle Pharmacokinetics: A Multi-View Learning Approach—0
Alternately Optimized Graph Neural Networks—0
A Multi-view Context-aware Approach to Android Malware Detection and Malicious Code Localization—0
A Multi-View Discriminant Learning Approach for Indoor Localization Using Bimodal Features of CSI—0
A Multi-View Dynamic Fusion Framework: How to Improve the Multimodal Brain Tumor Segmentation from Multi-Views?—0
A Multi-View Joint Learning Framework for Embedding Clinical Codes and Text Using Graph Neural Networks—0
A Multi-View Learning Approach to Enhance Automatic 12-Lead ECG Diagnosis Performance—0
A Multi-view Perspective of Self-supervised Learning—0
An introduction to R package `mvs`—0
Anomaly detecting and ranking of the cloud computing platform by multi-view learning—0
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