[1] TANG Kewei,SU Zhixun,JIANG Wei,et al.Robust subspace learning-based low-rank representation for manifold clustering[J].Neural Computing and Applications,2019,31(11):7921-7933. [2] ZHAO Xi,QIN Qianqing,LUO Bin.Motion segmentation based on model selection in permutation space for RGB sensors[J].Sensors,2019,19(13):1-15. [3] GUO Jiping,YIN Wenbin,SUN Yanfeng,et al.Multi-view subspace clustering with block diagonal representa-tion[J].IEEE Access,2019,7:84829-84838. [4] LIU Guangcan,LIN Zhouchen,YAN Shuicheng,et al.Robust recovery of subspace structures by low-rank representation[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2012,35(1):171-184. [5] GAO J,KANG M,TIAN J,et al.Unsupervised locality-preserving robust latent low-rank recovery-based subspace clustering for fault diagnosis[J].IEEE Access,2018,6:52345-52354. [6] ARIAS-CASTRO E,LERMAN G,ZHANG T.Spectral clustering based on local PCA[J].The Journal of Machine Learning Research,2017,18(1):253-309. [7] XU Xiaolong,WANG Shitong,MEI Xiangdong.Improved clustering algorithm based on local and global information[J].Computer Engineering,2015,41(6):165-171.(in Chinese)许小龙,王士同,梅向东.基于局部和全局信息的改进聚类算法[J].计算机工程,2015,41(6):165-171. [8] LI Xiaohong,XIE Meng,MA Huifang,et al.A short text clustering algorithm based on spectral cut[J].Computer Engineering,2016,42(8):178-182.(in Chinese)李晓红,谢蒙,马慧芳,等.一种基于谱分割的短文本聚类算法[J].计算机工程,2016,42(8):178-182. [9] ELHAMIFAR E,VIDAL R.Sparse subspace clustering:algorithm,theory,and applications[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2013,35(11):2765-2781. [10] LIU Guangcan,LIN Zhouchen,YU Yong.Robust subspace segmentation by low-rank representation[C]//Proceedings of the 27th International Conference on Machine Learning.Haifa,Israel:[s.n.],2010:663-670. [11] CHEN Jie,MAO Hua,SANG Yongsheng,et al.Subspace clustering using a symmetric low-rank representation[J].Knowledge-Based Systems,2017,127:46-57. [12] FANG Xiaozhao,HAN Na,WU Jigang,et al.Approximate low-rank projection learning for feature extraction[J].IEEE Transactions on Neural Networks and Learning Systems,2018,29(11):5228-5241. [13] WANG Qi,HE Xiang,LI Xuelong.Locality and structure regularized low rank representation for hyperspectral image classification[J].IEEE Transactions on Geoscience and Remote Sensing,2018,57(2):911-923. [14] NI Yuzhao,SUN Ju,YUAN Xiaotong,et al.Robust low-rank subspace segmentation with semidefinite guarantees[C]//Proceedings of 2010 IEEE International Conference on Data Mining.Washington D.C.,USA:IEEE Press,2010:1179-1188. [15] ZHUANG Liansheng,GAO Haoyuan,LIN Zhouchen,et al.Non-negative low rank and sparse graph for semi-supervised learning[C]//Proceedings of 2012 IEEE Conference on Computer Vision and Pattern Recognition.Washington D.C.,USA:IEEE Press,2012:2328-2335. [16] SHI J B,JITENDRA M.Normalized cuts and image segmentation[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,22(8):888-905. [17] TANG Kewei,LIU Risheng,SU Zhixun,et al.Structure-constrained low-rank representation[J].IEEE Transactions on Neural Networks and Learning Systems,2014,25(12):2167-2179. [18] TRON R,VIDAL R.A benchmark for the comparison of 3-D motion segmentation algorithms[C]//Proceedings of 2007 IEEE Conference on Computer Vision and Pattern Recognition.Washington D.C.,USA:IEEE Press,2007:1-8. [19] FENG Jiashi,LIN Zhouchen,XU Huan,et al.Robust subspace segmentation with block-diagonal prior[C]//Proceedings of 2014 IEEE Conference on Computer Vision and Pattern Recognition.Washington D.C.,USA:IEEE Press,2014:3818-3825. [20] YAN J Y,POLLEFEYS M.A general framework for motion segmentation:independent,articulated,rigid,non-rigid,degenerate and non-degenerate[C]//Proceedings of European Conference on Computer Vision.Berlin,Germany:Springer,2006:94-106. [21] VIDAL R,FAVARO P.Low rank subspace clustering[J].Pattern Recognition Letters,2014,43(1):47-61. |