[1]WANG Zhongyuan,LIU Jinglei.Kernel approximation of a low-rank block matrix[J].CAAI Transactions on Intelligent Systems,2019,14(6):1209-1216.[doi:10.11992/tis.201904058]
Copy

Kernel approximation of a low-rank block matrix

References:
[1] 雷恒鑫, 刘惊雷. 基于行列联合选择矩阵分解的偏好特征提取[J]. 模式识别与人工智能, 2017, 30(3):279-288 LEI Hengxin, LIU Jinglei. Preference feature extraction based on column union row matrix decomposition[J]. Pattern recognition and artificial intelligence, 2017, 30(3):279-288
[2] 张恒敏, 杨健, 郑玮. 低秩矩阵近似与优化问题研究进展[J]. 模式识别与人工智能, 2018, 31(1):23-36 ZHANG Hengmin, YANG Jian, ZHENG Wei. Research progress of low-rank matrix approximation and optimization problem[J]. Pattern recognition and artificial intelligence, 2018, 31(1):23-36
[3] CHIANG K Y, DHILLON I S, HSIEH C J. Using side information to reliably learn low-rank matrices from missing and corrupted observations[J]. Journal of machine learning research, 2018, 19(76):1-35.
[4] LU Canyi, FENG Jiashi, LIN Zhouchen. Subspace clustering by block diagonal representation[J]. IEEE transactions on pattern analysis and machine intelligence, 2019, 41(2):487-501.
[5] ZHANG Zheng, XU Yong, SHAO Ling. Discriminative block-diagonal representation learning for image recognition[J]. IEEE transactions on neural networks and learning systems, 2018, 29(7):3111-3125.
[6] WEI C P, CHEN C F, WANG Y C F. Robust face recognition with structurally incoherent low-rank matrix decomposition[J]. IEEE transactions on image processing, 2014, 23(8):3294-3307.
[7] 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 Workshops. Sydney, NSW, Australia, 2010:1179-1188.
[8] LEE K C, HO J, KRIEGMAN D J. Acquiring linear subspaces for face recognition under variable lighting[J]. IEEE transactions on pattern analysis and machine intelligence, 2005, 27(5):684-698.
[9] CANDèS E J, LI Xiaodong, MA Yi. Robust principal component analysis?[J]. Journal of the ACM, 2011, 58(3):11.
[10] LIU Guangcan, LIN Zhouchen, YAN Shuicheng. Robust recovery of subspace structures by low-rank representation[J]. IEEE transactions on pattern analysis and machine intelligence, 2013, 35(1):171-184.
[11] CHEN Yudong, JALALI A, SANGHAVI S, et al. Clustering partially observed graphs via convex optimization[J]. The journal of machine learning research, 2014, 15(1):2213-2238.
[12] LIN Zhouchen, CHEN Minming, MA Yi. The augmented lagrange multiplier method for exact recovery of corrupted low-rank matrices[J]. arXiv preprint arXiv:1009.5055, 2010.
[13] LU Canyi, FENG Jiashi, YAN Shuicheng. A unified alternating direction method of multipliers by majorization minimization[J]. IEEE transactions on pattern analysis and machine intelligence, 2018, 40(3):527-541.
[14] 刘松华, 张军英, 丁彩英. 核矩阵列相关低秩近似分解算法[J]. 模式识别与人工智能, 2011, 24(6):776-782 LIU Songhua, ZHAGN Junying, DING Caiying. Low-Rank approximation and decomposition for kernel matrix based on column correlation[J]. Pattern recognition and artificial intelligence, 2011, 24(6):776-782
[15] YIN Ming, GAO Junbin, LIN Zhouchen. Laplacian regularized low-rank representation and its applications[J]. IEEE transactions on pattern analysis and machine intelligence, 2016, 38(3):504-517.
[16] HE Xiaofei, CAI Deng, SHAO Yuanlong, et al. Laplacian regularized Gaussian mixture model for data clustering[J]. IEEE transactions on knowledge and data engineering, 2011, 23(9):1406-1418.
[17] NASEEM I, TOGNERI R, BENNAMOUN M. Linear regression for face recognition[J]. IEEE transactions on pattern analysis and machine intelligence, 2010, 32(11):2106-2112.
[18] 丁立中, 廖士中. KMA-α:一个支持向量机核矩阵的近似计算算法[J]. 计算机研究与发展, 2012, 49(4):746-753 DING Lizhong, LIAO Shizhong. KMA-α:a kernel matrix approximation algorithm for support vector machines[J]. Journal of computer research and development, 2012, 49(4):746-753
[19] TIAN Shangxuan, LU Shijian, SU Bolan. Scene text recognition using co-occurrence of histogram of oriented gradients[C]//Proceedings of the 12th International Conference on Document Analysis and Recognition. Washington, DC, USA, 2013:912-916.
[20] PHAN T Q, SHIVAKUMARA P, TIAN S X. Recognizing text with perspective distortion in natural scenes[C]//Proceedings of 2013 IEEE International Conference on Computer Vision. Sydney, NSW, Australia, 2013:569-576.
[21] TAN Zhirong, TIAN Shangxuan, TAN C L. Using pyramid of histogram of oriented gradients on natural scene text recognition[C]//Proceedings of 2014 IEEE International Conference on Image Processing. Paris, France, 2014:2629-2633.
[22] LEE C Y, BHARDWAJ A, DI Wei, et al. Region-based discriminative feature pooling for scene text recognition[C]//Proceedings of 2014 IEEE Conference on Computer Vision and Pattern Recognition. Columbus, OH, USA, 2014:4050-4057.
Similar References:

Memo

-

Last Update: 2019-12-25

Copyright © CAAI Transactions on Intelligent Systems