diff --git a/README.md b/README.md index 7f5a875..e2df493 100644 --- a/README.md +++ b/README.md @@ -16,17 +16,17 @@ We are looking forward for other participants to share their papers and codes. I - [Benchmark Datasets](#jump3) - [Oringinal Datasets](#jump31) - [Kernelized Datasets](#jump32) +- [Scholars](#jump4) --- ## Important Survey Papers -1. A survey on multi-view learning [Paper](https://arxiv.org/pdf/1304.5634) +1. Xu, Chang, Dacheng Tao, and Chao Xu. "A survey on multi-view learning" (2013) cited by: 897 [[Paper]](https://arxiv.org/pdf/1304.5634) +2. Wang, Hao, et al. "A study of graph-based system for multi-view clustering" (2019) cited by: 102 [[Paper]](https://www.researchgate.net/profile/Hao_Wang250/publication/328573967_A_study_of_graph-based_system_for_multi-view_clustering/links/5cbff7e5299bf120977adaa6/A-study-of-graph-based-system-for-multi-view-clustering.pdf) [[code]](https://github.com/cswanghao/gbs) +3. Yang, Yan, and Hao Wang. "Multi-view clustering: A survey" (2018) cited by: 117 [[Paper]](https://ieeexplore.ieee.org/iel7/8254253/8336843/08336846.pdf) +4. Zhao, Jing, et al. "Multi-view learning overview: Recent progress and new challenges" (2017) cited by: 419 [[Paper]](https://www.researchgate.net/profile/Shiliang_Sun2/publication/314251895_Multi-view_Learning_Overview_Recent_Progress_and_New_Challenges/links/5def9d8f92851c836470978c/Multi-view-Learning-Overview-Recent-Progress-and-New-Challenges.pdf) -1. A study of graph-based system for multi-view clustering [Paper](https://www.researchgate.net/profile/Hao_Wang250/publication/328573967_A_study_of_graph-based_system_for_multi-view_clustering/links/5cbff7e5299bf120977adaa6/A-study-of-graph-based-system-for-multi-view-clustering.pdf) [code](https://github.com/cswanghao/gbs) - -1. Multi-view clustering: A survey [Paper](https://ieeexplore.ieee.org/iel7/8254253/8336843/08336846.pdf) - -1. Multi-view learning overview: Recent progress and new challenges [Paper](https://www.researchgate.net/profile/Shiliang_Sun2/publication/314251895_Multi-view_Learning_Overview_Recent_Progress_and_New_Challenges/links/5def9d8f92851c836470978c/Multi-view-Learning-Overview-Recent-Progress-and-New-Challenges.pdf) +**Note:** The number of citation was calculated by Google Scholar until 15th June. 2021. --- @@ -34,62 +34,92 @@ We are looking forward for other participants to share their papers and codes. I Papers are listed in the following methods:graph clustering, NMF-based clustering, co-regularized, subspace clustering and multi-kernel clustering ### Graph Clusteirng -1. AAAI15: Large-Scale Multi-View Spectral Clustering via Bipartite Graph [Paper](https://www.aaai.org/ocs/index.php/AAAI/AAAI15/paper/download/9641/9937) [code](https://github.com/zzz123xyz/MVSC) -1. IJCAI17: Self-Weighted Multiview Clustering with Multiple Graphs" [Paper](https://www.ijcai.org/Proceedings/2017/0357.pdf) [code](https://github.com/kylejingli/SwMC-IJCAI17) +- AAAI15: + 1. Li, Yeqing, et al. "Large-Scale Multi-View Spectral Clustering via Bipartite Graph" [[Paper]](https://www.aaai.org/ocs/index.php/AAAI/AAAI15/paper/download/9641/9937) [[code]](https://github.com/zzz123xyz/MVSC) + +- IJCAI17: + 1. Nie, Feiping, Jing Li, and Xuelong Li. "Self-Weighted Multiview Clustering with Multiple Graphs" [[Paper]](https://www.ijcai.org/Proceedings/2017/0357.pdf) [[code]](https://github.com/kylejingli/SwMC-IJCAI17) -1. TKDE2018： One-step multi-view spectral clustering [Paper](https://ieeexplore.ieee.org/abstract/document/8478288/) [code](https://pan.baidu.com/s/1eFiB87O0LBkJS8ZRSybNfQ) +- TKDE2018： + 1. Zhu, Xiaofeng, et al. "One-step multi-view spectral clustering" [[Paper]](https://ieeexplore.ieee.org/abstract/document/8478288/) [[code]](https://pan.baidu.com/s/1eFiB87O0LBkJS8ZRSybNfQ) -1. TKDE19: GMC: Graph-based Multi-view Clustering [Paper](https://ieeexplore.ieee.org/abstract/document/8662703) [code](https://github.com/cshaowang/gmc) +- TKDE19: + 1. Wang, Hao, Yan Yang, and Bing Liu. "GMC: Graph-based Multi-view Clustering" [[Paper]](https://ieeexplore.ieee.org/abstract/document/8662703) [[code]](https://github.com/cshaowang/gmc) -1. ICDM2019: Consistency Meets Inconsistency: A Unified Graph Learning Framework for Multi-view Clustering [Paper](https://www.researchgate.net/profile/Dong_Huang9/publication/335857675_Consistency_Meets_Inconsistency_A_Unified_Graph_Learning_Framework_for_Multi-view_Clustering/links/5d809ca7458515fca16e3776/Consistency-Meets-Inconsistency-A-Unified-Graph-Learning-Framework-for-Multi-view-Clustering.pdf) [code](https://github.com/youweiliang/ConsistentGraphLearning) +- ICDM2019: + 1. Liang, Youwei, Dong Huang, and Chang-Dong Wang. "Consistency Meets Inconsistency: A Unified Graph Learning Framework for Multi-view Clustering" [[Paper]](https://www.researchgate.net/profile/Dong_Huang9/publication/335857675_Consistency_Meets_Inconsistency_A_Unified_Graph_Learning_Framework_for_Multi-view_Clustering/links/5d809ca7458515fca16e3776/Consistency-Meets-Inconsistency-A-Unified-Graph-Learning-Framework-for-Multi-view-Clustering.pdf) [[code]](https://github.com/youweiliang/ConsistentGraphLearning) ### Multiple Kenrel Clustering(MKC) -1. NIPS14: Localized Data Fusion for Kernel k-Means Clustering with Application to Cancer Biology [Paper](https://papers.nips.cc/paper/5236-localized-data-fusion-for-kernel-k-means-clustering-with-application-to-cancer-biology.pdf) [code](https://github.com/mehmetgonen/lmkkmeans) +- NIPS14: + 1. Gönen, Mehmet, and Adam A. Margolin. "Localized Data Fusion for Kernel k-Means Clustering with Application to Cancer Biology" [[Paper]](https://papers.nips.cc/paper/5236-localized-data-fusion-for-kernel-k-means-clustering-with-application-to-cancer-biology.pdf) [[code]](https://github.com/mehmetgonen/lmkkmeans) -1. IJCAI15： Robust Multiple Kernel K-means using L21-norm [Paper](https://www.aaai.org/ocs/index.php/IJCAI/IJCAI15/paper/download/11332/11224) [code](https://github.com/csliangdu/RMKKM) +- IJCAI15： + 1. Du, Liang, et al. "Robust Multiple Kernel K-means using L21-norm" [[Paper]](https://www.aaai.org/ocs/index.php/IJCAI/IJCAI15/paper/download/11332/11224) [[code]](https://github.com/csliangdu/RMKKM) -1. AAAI16：Multiple Kernel k-Means Clustering with Matrix-Induced Regularization [Paper](https://www.aaai.org/ocs/index.php/AAAI/AAAI16/paper/viewPDFInterstitial/12115/11819) [code](https://github.com/wangsiwei2010/Multiple-Kernel-k-Means-Clustering-with-Matrix-Induced-Regularization) +- AAAI16： + 1. Liu, Xinwang, et al. "Multiple Kernel k-Means Clustering with Matrix-Induced Regularization" [[Paper]](https://www.aaai.org/ocs/index.php/AAAI/AAAI16/paper/viewPDFInterstitial/12115/11819) [[code]](https://github.com/wangsiwei2010/Multiple-Kernel-k-Means-Clustering-with-Matrix-Induced-Regularization) -1. IJCAI19: Multi-view Clustering with Late Fusion Alignment Maximization [Paper](https://www.ijcai.org/proceedings/2019/0524.pdf) [code](https://github.com/wangsiwei2010/latefusionalignment) +- IJCAI19: + 1. Wang, Siwei, et al. "Multi-view Clustering with Late Fusion Alignment Maximization" [[Paper]](https://www.ijcai.org/proceedings/2019/0524.pdf) [[code]](https://github.com/wangsiwei2010/latefusionalignment) -1. TNNLS2019: Multiple kernel clustering with neighbor-kernel subspace segmentation [Paper](https://ieeexplore.ieee.org/document/8750871) [code](https://github.com/SihangZhou/Demo-of-Multiple-Kernel-Clustering-with-Neighbor-Kernel-Subspace-Segmentation) +- TNNLS2019: + 1. Zhou, Sihang, et al. "Multiple kernel clustering with neighbor-kernel subspace segmentation" [[Paper]](https://ieeexplore.ieee.org/document/8750871) [[code]](https://github.com/SihangZhou/Demo-of-Multiple-Kernel-Clustering-with-Neighbor-Kernel-Subspace-Segmentation) ### Subspace Clustering -1. CVPR2015 Diversity-induced Multi-view Subspace Clustering [Paper](https://www.zpascal.net/cvpr2015/Cao_Diversity-Induced_Multi-View_Subspace_2015_CVPR_paper.pdf) [code](http://cic.tju.edu.cn/faculty/zhangchangqing/code/DiMSC.rar) +- CVPR2015: + 1. Cao, Xiaochun, et al. "Diversity-induced Multi-view Subspace Clustering" [[Paper]](https://www.zpascal.net/cvpr2015/Cao_Diversity-Induced_Multi-View_Subspace_2015_CVPR_paper.pdf) [[code]](http://cic.tju.edu.cn/faculty/zhangchangqing/code/DiMSC.rar) -1. CVPR2017 Latent Multi-view Subspace Clustering [Paper](http://cic.tju.edu.cn/faculty/zhangchangqing/pub/Zhang_Latent_Multi-View_Subspace_CVPR_2017_paper.pdf) [code](http://cic.tju.edu.cn/faculty/zhangchangqing/code/LMSC_CVPR2017_Zhang.rar) +- CVPR2017: + 1. Zhang, Changqing, et al. "Latent Multi-view Subspace Clustering" [[Paper]](http://cic.tju.edu.cn/faculty/zhangchangqing/pub/Zhang_Latent_Multi-View_Subspace_CVPR_2017_paper.pdf) [[code]](http://cic.tju.edu.cn/faculty/zhangchangqing/code/LMSC_CVPR2017_Zhang.rar) -1. AAAI2018 Consistent and Specific Multi-view Subspace Clustering [Paper](https://github.com/XIAOCHUN-CAS/Academic-Publications/blob/master/Conference/2018_AAAI_Luo.pdf) [code](https://github.com/XIAOCHUN-CAS/Consistent-and-Specific-Multi-View-Subspace-Clustering) +- AAAI2018: + 1. Luo, Shirui, et al. "Consistent and Specific Multi-view Subspace Clustering" [[Paper]](https://github.com/XIAOCHUN-CAS/Academic-Publications/blob/master/Conference/2018_AAAI_Luo.pdf) [[code]](https://github.com/XIAOCHUN-CAS/Consistent-and-Specific-Multi-View-Subspace-Clustering) -1. PR2018: Multi-view Low-rank Sparse Subspace Clustering [Paper](https://arxiv.org/abs/1708.08732) [code](https://github.com/wangsiwei2010/Multi-view-LRSSC) +- PR2018: + 1. Brbić, Maria, and Ivica Kopriva. "Multi-view Low-rank Sparse Subspace Clustering" [[Paper]](https://arxiv.org/abs/1708.08732) [[code]](https://github.com/wangsiwei2010/Multi-view-LRSSC) -1. TIP2019: Split Multiplicative Multi-view Subspace Clustering [Paper](https://www.researchgate.net/publication/333007034_Split_Multiplicative_Multi-view_Subspace_Clustering) [code](https://github.com/joshuaas/SM2SC) +- TIP2019: + 1. Yang, Zhiyong, et al. "Split Multiplicative Multi-view Subspace Clustering" [[Paper]](https://www.researchgate.net/publication/333007034_Split_Multiplicative_Multi-view_Subspace_Clustering) [[code]](https://github.com/joshuaas/SM2SC) -1. IJCAI19: Flexible multi-view representation learning for subspace clustering [Paper](https://www.ijcai.org/Proceedings/2019/0404.pdf) [code](https://github.com/lslrh/FMR) +- IJCAI19: + 1. Li, Ruihuang, et al. "Flexible multi-view representation learning for subspace clustering" [[Paper]](https://www.ijcai.org/Proceedings/2019/0404.pdf) [[code]](https://github.com/lslrh/FMR) -1. ICCV19: Reciprocal Multi-Layer Subspace Learning for Multi-View Clustering [Paper](http://openaccess.thecvf.com/content_ICCV_2019/papers/Li_Reciprocal_Multi-Layer_Subspace_Learning_for_Multi-View_Clustering_ICCV_2019_paper.pdf) [code](https://github.com/lslrh/RMSL) +- ICCV19: + 1. Li, Ruihuang, et al. "Reciprocal Multi-Layer Subspace Learning for Multi-View Clustering" [[Paper]](http://openaccess.thecvf.com/content_ICCV_2019/papers/Li_Reciprocal_Multi-Layer_Subspace_Learning_for_Multi-View_Clustering_ICCV_2019_paper.pdf) [[code]](https://github.com/lslrh/RMSL) ### Deep Multi-view Clustering -1. CVPR2019: AE^2-Nets: Autoencoder in Autoencoder Networks [Paper](http://cic.tju.edu.cn/faculty/zhangchangqing/pub/AE2_Nets.pdf) [code](https://github.com/willow617/AE2-Nets) -2. TIP2019: Multi-view Deep Subspace Clustering Networks [Paper](https://arxiv.org/abs/1908.01978) [code](https://github.com/huybery/MvDSCN) -3. TKDE2020: Joint Deep Multi-View Learning for Image Clustering [Paper](https://ieeexplore.ieee.org/abstract/document/8999493/) -4. ICML2019: COMIC: Multi-view Clustering Without Parameter Selection [paper](http://proceedings.mlr.press/v97/peng19a/peng19a.pdf) [code](https://github.com/limit-scu/2019-ICML-COMIC) -5. IJCAI2019: Multi-view Spectral Clustering Network [paper](https://www.ijcai.org/Proceedings/2019/0356.pdf) [code](https://github.com/limit-scu/2019-IJCAI-MvSCN) -6. IJCAI2019: Deep Adversarial Multi-view Clustering Network [paper](https://www.ijcai.org/Proceedings/2019/0409.pdf) [code](https://github.com/IMKBLE/DAMC) +- CVPR2019: + 1. Zhang, Changqing, Yeqing Liu, and Huazhu Fu. "AE^2-Nets: Autoencoder in Autoencoder Networks" [[Paper]](http://cic.tju.edu.cn/faculty/zhangchangqing/pub/AE2_Nets.pdf) [[code]](https://github.com/willow617/AE2-Nets) + +- TIP2019: + 1. Zhu, Pengfei, et al. "Multi-view Deep Subspace Clustering Networks" [[Paper]](https://arxiv.org/abs/1908.01978) [[code]](https://github.com/huybery/MvDSCN) + +- ICML2019: + 1. Peng, Xi, et al. "COMIC: Multi-view Clustering Without Parameter Selection" [[paper]](http://proceedings.mlr.press/v97/peng19a/peng19a.pdf) [[code]](https://github.com/limit-scu/2019-ICML-COMIC) + +- IJCAI2019: + 1. Huang, Zhenyu, et al. "Multi-view Spectral Clustering Network" [[paper]](https://www.ijcai.org/Proceedings/2019/0356.pdf) [[code]](https://github.com/limit-scu/2019-IJCAI-MvSCN) + 2. Li, Zhaoyang, et al. "Deep Adversarial Multi-view Clustering Network" [[paper]](https://www.ijcai.org/Proceedings/2019/0409.pdf) [[code]](https://github.com/IMKBLE/DAMC) + +- TKDE2020: + 1. Xie, Yuan, et al. "Joint Deep Multi-View Learning for Image Clustering" [[Paper]](https://ieeexplore.ieee.org/abstract/document/8999493/) ### Binary Multi-view Clustering -1. TPAMI2019: Binary Multi-View Clustering [Paper](http://cfm.uestc.edu.cn/~fshen/TPAMI-BMVC_Final.pdf) [code](https://github.com/DarrenZZhang/BMVC) +- TPAMI2019: + 1. Zhang, Zheng, et al. "Binary Multi-View Clustering" [[Paper]](http://cfm.uestc.edu.cn/~fshen/TPAMI-BMVC_Final.pdf) [[code]](https://github.com/DarrenZZhang/BMVC) ### NMF-based Multi-view Clustering -1. AAAI20: Multi-view Clustering in Latent Embedding Space [Paper](https://www.researchgate.net/profile/Dong_Huang9/publication/338883065_Multi-view_Clustering_in_Latent_Embedding_Space/links/5e30e4ee458515072d6ab048/Multi-view-Clustering-in-Latent-Embedding-Space.pdf?_sg%5B0%5D=c7_LGDqrWNZ_2R_YVqZW5paGs4aiAWHyL5Vm6D9xC-qLrwZgnT5PnHd5qcLIWLjUU1w1sMRvcFieskwMXfiUxA.C7MpmX3wox2zTGV_rHjWvJVYUcWBn5cx271Yud84FlPQiu_W8azOItQWDVbvUiM3bw4kxI_zLS8mGKTKMl5f3w&_sg%5B1%5D=Ug4z3sxpjLL5fvIFDmpbr9hht6CQIYTxXEPWuPHRJZvOOuGvEI2QyxzM8WX0M3c0SkQeyoVq3fnE9kyqH5TWHTslmLrQDWSN3t6xvMVZkLTi.C7MpmX3wox2zTGV_rHjWvJVYUcWBn5cx271Yud84FlPQiu_W8azOItQWDVbvUiM3bw4kxI_zLS8mGKTKMl5f3w&_iepl=) [code](https://github.com/Ttuo123/MCLES) +- AAAI20: + 1. Chen, Man-Sheng, et al. "Multi-view Clustering in Latent Embedding Space" [[Paper]](https://www.researchgate.net/profile/Dong_Huang9/publication/338883065_Multi-view_Clustering_in_Latent_Embedding_Space/links/5e30e4ee458515072d6ab048/Multi-view-Clustering-in-Latent-Embedding-Space.pdf?_sg%5B0%5D=c7_LGDqrWNZ_2R_YVqZW5paGs4aiAWHyL5Vm6D9xC-qLrwZgnT5PnHd5qcLIWLjUU1w1sMRvcFieskwMXfiUxA.C7MpmX3wox2zTGV_rHjWvJVYUcWBn5cx271Yud84FlPQiu_W8azOItQWDVbvUiM3bw4kxI_zLS8mGKTKMl5f3w&_sg%5B1%5D=Ug4z3sxpjLL5fvIFDmpbr9hht6CQIYTxXEPWuPHRJZvOOuGvEI2QyxzM8WX0M3c0SkQeyoVq3fnE9kyqH5TWHTslmLrQDWSN3t6xvMVZkLTi.C7MpmX3wox2zTGV_rHjWvJVYUcWBn5cx271Yud84FlPQiu_W8azOItQWDVbvUiM3bw4kxI_zLS8mGKTKMl5f3w&_iepl=) [[code]](https://github.com/Ttuo123/MCLES) ### Ensemble-based Multi-view Clustering -1. TNNLS2019: Marginalized Multiview Ensemble Clustering [Paper](https://ieeexplore.ieee.org/document/8691702) [code](https://pan.baidu.com/s/1ipfGlQKcBTQn71yP3ZbISQ) +- TNNLS2019: + 1. Tao, Zhiqiang, et al. "Marginalized Multiview Ensemble Clustering" [[Paper]](https://ieeexplore.ieee.org/document/8691702) [[code]](https://pan.baidu.com/s/1ipfGlQKcBTQn71yP3ZbISQ) @@ -134,3 +164,11 @@ If you use our code or datasets, please cite our with the following bibtex code } ``` +--- + +## Scholars + +- [Feiping Nie](https://sites.google.com/site/feipingnie/publications), from Tsinghua University, cited by 22874 +- [Xinwang Liu](https://xinwangliu.github.io/), from National University of Defense Technology (NUDT), cited by 4133. +- [Changqing Zhang](http://cic.tju.edu.cn/faculty/zhangchangqing/research.html), from Tianjin University, cited by 3096. +- [Xi Peng](http://pengxi.me/), from Sichuan Univeristy (SCU), cited by 2460. diff --git a/Untitled Diagram.drawio b/Untitled Diagram.drawio new file mode 100644 index 0000000..117fd98 --- /dev/null +++ b/Untitled Diagram.drawio @@ -0,0 +1 @@ +UzV2zq1wL0osyPDNT0nNUTV2VTV2LsrPL4GwciucU3NyVI0MMlNUjV1UjYwMgFjVyA2HrCFY1qAgsSg1rwSLBiADYTaQg2Y1AA== \ No newline at end of file