Collections for state-of-the-art (SOTA), novel multi-view clustering methods (papers, codes and datasets)
We are looking forward for other participants to share their papers and codes. If interested, please contanct wangsiwei13@nudt.edu.cn.
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A survey on multi-view learning Paper
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A study of graph-based system for multi-view clustering Paper code
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Multi-view clustering: A survey Paper
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Multi-view learning overview: Recent progress and new challenges Paper
Papers are listed in the following methods:graph clustering, NMF-based clustering, co-regularized, subspace clustering and multi-kernel clustering
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AAAI15: Large-Scale Multi-View Spectral Clustering via Bipartite Graph Paper code
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IJCAI17: Self-Weighted Multiview Clustering with Multiple Graphs" Paper code
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TKDE2018: One-step multi-view spectral clustering Paper code
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ICDM2019: Consistency Meets Inconsistency: A Unified Graph Learning Framework for Multi-view Clustering Paper code
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TMM 2021: Consensus Graph Learning for Multi-view Clustering code
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NIPS14: Localized Data Fusion for Kernel k-Means Clustering with Application to Cancer Biology Paper code
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IJCAI15: Robust Multiple Kernel K-means using L21-norm Paper code
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AAAI16:Multiple Kernel k-Means Clustering with Matrix-Induced Regularization Paper code
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IJCAI19: Multi-view Clustering with Late Fusion Alignment Maximization Paper code
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TNNLS2019: Multiple kernel clustering with neighbor-kernel subspace segmentation Paper code
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CVPR2015 Diversity-induced Multi-view Subspace Clustering Paper code
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AAAI2018 Consistent and Specific Multi-view Subspace Clustering Paper code
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PR2018: Multi-view Low-rank Sparse Subspace Clustering Paper code
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TIP2019: Split Multiplicative Multi-view Subspace Clustering Paper code
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IJCAI19: Flexible multi-view representation learning for subspace clustering Paper code
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ICCV19: Reciprocal Multi-Layer Subspace Learning for Multi-View Clustering Paper code
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CVPR2019: AE^2-Nets: Autoencoder in Autoencoder Networks Paper code
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TIP2019: Multi-view Deep Subspace Clustering Networks Paper code
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TKDE2020: Joint Deep Multi-View Learning for Image Clustering Paper
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ICML2019: COMIC: Multi-view Clustering Without Parameter Selection paper code
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IJCAI2019: Multi-view Spectral Clustering Network paper code
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IJCAI2019: Deep Adversarial Multi-view Clustering Network paper code
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KBS2021:Multi-view clustering via deep concept factorization code
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TPAMI 2021: Multi-view Clustering: A Scalable and Parameter-free Bipartite Graph Fusion Method Paper code
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AAAI20: arge-scale Multi-view Subspace Clustering in Linear Time paper code
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ACM MM2021: Scalable Multi-view Subspace Clustering with Unified Anchors paper code
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AAAI22: Efficient One-pass Multi-view Subspace Clustering with Consensus Anchors code
- Applied Soft Computing 2021: An Evolutionary Many-objective Approach to Multiview Clustering Using Feature and Relational Data Paper code
- It contains seven widely-used multi-view datasets: Handwritten (HW), Caltech-7/20, BBCsports, Nuswide, ORL and Webkb. Released by Baidu Service. address (code)gaih
- The following kernelized datasets are created by our team. For more information, you can ask wangsiwei13@nudt.edu.cn for help. address (code)y44e
If you use our code or datasets, please cite our with the following bibtex code :
@inproceedings{wang2019multi,
title={Multi-view clustering via late fusion alignment maximization},
author={Wang, Siwei and Liu, Xinwang and Zhu, En and Tang, Chang and Liu, Jiyuan and Hu, Jingtao and Xia, Jingyuan and Yin, Jianping},
booktitle={Proceedings of the 28th International Joint Conference on Artificial Intelligence},
pages={3778--3784},
year={2019},
organization={AAAI Press}
}