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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 151–160 of 256 papers

TitleStatusHype
A Novel Random Forest Dissimilarity Measure for Multi-View Learning—0
Deep brain state classification of MEG dataCode0
A Tweet-based Dataset for Company-Level Stock Return PredictionCode0
Multi-view Low-rank Preserving Embedding: A Novel Method for Multi-view Representation—0
Hierarchical Optimal Transport for Robust Multi-View Learning—0
Bayesian Sparse Factor Analysis with Kernelized Observations—0
Deep Tensor CCA for Multi-view LearningCode1
Generalized Multi-view Shared Subspace Learning using View Bootstrapping—0
A Solution for Large Scale Nonlinear Regression with High Rank and Degree at Constant Memory Complexity via Latent Tensor Reconstruction—0
SleepPoseNet: Multi-View Learning for Sleep Postural Transition Recognition Using UWBCode1
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