/Awesome-Semi-supervised-Multi-view-classification

Awesome Semi-supervised Multi-view Classification is a collection of SOTA, novel semi-supervised multi-view classification methods (papers, codes).

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Awesome-Semi-supervised-Multi-view-classification(SSMVC)

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Collections for Awesome-Semi-supervised-Multi-view-classification methods (papers and codes). We are looking forward for other participants to share their papers and codes. If interested, please contact wanxinhang@nudt.edu.cn.

Update at May 2024.

Content

Graph SSMVC

Paper Year Publish PDF Code
Generative Essential Graph Convolutional Network for Multi-view Semi-supervised Classification (GEGCN) 2024 TMM link python
Label-Weighted Graph-Based Learning for Semi-Supervised Classification Under Label Noise (LWGL) 2024 TBD link -
Learnable Graph Convolutional Network and Feature Fusion for Multi-view Learning (LGCN-FF) 2023 Inform Fusion link python
Joint learning of feature and topology for multi-view graph convolutional network (JFGCN) 2023 NN link python
Interpretable Graph Convolutional Network for Multi-View Semi-Supervised Learning (IMvGCN) 2023 TMM link python
Fast Multi-View Semi-Supervised Learning With Learned Graph (FMSSL) 2022 TKDE link matlab
Semi-Supervised and Self-Supervised Classification with Multi-View Graph Neural Networks (MV-CGC) 2021 CIKM link -
Co-GCN for Multi-View Semi-Supervised Learning (Co-GCN) 2020 AAAI link python
Latent Multi-view Semi-Supervised Classification (LMSSC) 2019 ACML link matlab
Multi-View Clustering and Semi-Supervised Classification with Adaptive Neighbours (MLAN) 2017 AAAI link matlab
Scalable Multi-View Semi-Supervised Classification via Adaptive Regression (MVAR) 2017 TIP link matlab
Parameter-Free Auto-Weighted Multiple Graph Learning: A Framework for Multiview Clustering and Semi-Supervised Classification (AMGL) 2016 IJCAI link matlab

Depresentation Learning SSMVC

Paper Year Publish PDF Code
Learning Deep Sparse Regularizers With Applications to Multi-View Clustering and Semi-Supervised Classification (DSRL) 2022 TPAMI link python
A semi-supervised label-driven auto-weighted strategy for multi-view data classification (LACK) 2022 KBS link matlab
MMatch: Semi-Supervised Discriminative Representation Learning for Multi-View Classification (MMatch) 2022 TCSVT link -
Semi-Supervised Multi-View Deep Discriminant Representation Learning (SMDDRL) 2021 TPAMI link -
Embedding Regularizer Learning for Multi-View Semi-Supervised Classification (ERL-MVSC) 2021 TIP link matlab

NMF-based SSMVC

Paper Year Publish PDF Code
Label prediction based constrained non-negative matrix factorization for semi-supervised multi-view classification (LPCNMF) 2022 Neurocomputing link -
Co-consensus semi-supervised multi-view learning with orthogonal non-negative matrix factorization (CONMF) 2022 INFORM PROCESS MANAG link matlab
Semi-supervised multi-view learning by using label propagation based non-negative matrix factorization (LPNMF) 2021 KBS link -
Semi-supervised multi-view clustering with Graph-regularized Partially Shared Non-negative Matrix Factorization (GPSNMF) 2020 KBS link matlab

Other Methods

Paper Year Publish PDF Code
Decouple then Classify: A Dynamic Multi-view Labeling Strategy with Shared and Specific Information (DMVLS) 2024 ICML link python
Seeded random walk for multi-view semi-supervised classification (SRW-MSC) 2022 KBS link -
Generative View-Correlation Adaptation for Semi-supervised Multi-view Learning (GVCA) 2020 ECCV link python
Multiview Classification With Cohesion and Diversity (MCCD) 2020 TCYB link matlab
Joint consensus and diversity for multi-view semi-supervised classification (JCD) 2020 Machine Learning link matlab

Multi-view-clustering-links:

https://github.com/wanxinhang/Awesome-Continual-Multi-view-clustering

https://github.com/dugzzuli/A-Survey-of-Multi-view-Clustering-Approaches#the-information-fusion-strategy

https://github.com/wangsiwei2010/awesome-multi-view-clustering

https://github.com/liangnaiyao/multiview_learning

Citations:

@inproceedings{wan2024decouple, title={Decouple then Classify: A Dynamic Multi-view Labeling Strategy with Shared and Specific Information}, author={Wan, Xinhang and Liu, Jiyuan and Liu, Xinwang and Wen, Yi and Yu, Hao and Wang, Siwei and Yu, Shengju and Wan, Tianjiao and Wang, Jun and Zhu, En}, booktitle={Forty-first International Conference on Machine Learning}, year={2024} }

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