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2020 – today
- 2023
[j8]Xiang-Fei Yang
, Mengyi Zheng, Li-Ming Liu:
Robust Two-Dimensional T$\ell _{1}$-Norm Linear Discriminant Analysis for Image Recognition. IEEE Signal Process. Lett. 30: 523-527 (2023)- 2021
- [j7]Zhen Wang, Yuan-Hai Shao, Lan Bai, Chun-Na Li, Li-Ming Liu:
General Plane-Based Clustering With Distribution Loss. IEEE Trans. Neural Networks Learn. Syst. 32(9): 3880-3893 (2021) - 2020
- [i3]Xiang-Fei Yang, Yuan-Hai Shao, Chun-Na Li, Li-Ming Liu, Nai-Yang Deng:
Principal Component Analysis Based on T𝓁1-norm Maximization. CoRR abs/2005.12263 (2020)
2010 – 2019
- 2019
- [j6]Chun-Na Li, Meng-Qi Shang, Yuan-Hai Shao, Yan Xu, Li-Ming Liu, Zhen Wang:
Sparse L1-norm two dimensional linear discriminant analysis via the generalized elastic net regularization. Neurocomputing 337: 80-96 (2019) - [i2]Zhen Wang, Yuan-Hai Shao, Lan Bai, Chun-Na Li, Li-Ming Liu:
A general model for plane-based clustering with loss function. CoRR abs/1901.09178 (2019) - 2018
- [j5]Zhen Wang, Yuan-Hai Shao, Lan Bai, Chun-Na Li, Li-Ming Liu, Nai-Yang Deng:
Insensitive stochastic gradient twin support vector machines for large scale problems. Inf. Sci. 462: 114-131 (2018) - 2017
- [j4]Li-Ming Liu, Yan-Ru Guo, Zhen Wang, Zhi-Min Yang, Yuan-Hai Shao:
k-Proximal plane clustering. Int. J. Mach. Learn. Cybern. 8(5): 1537-1554 (2017) - [i1]Zhen Wang, Yuan-Hai Shao, Lan Bai, Li-Ming Liu, Nai-Yang Deng:
Stochastic Gradient Twin Support Vector Machine for Large Scale Problems. CoRR abs/1704.05596 (2017) - 2016
- [j3]Zhen Wang, Yuan-Hai Shao, Lan Bai, Chun-Na Li, Li-Ming Liu, Nai-Yang Deng:
MBLDA: A novel multiple between-class linear discriminant analysis. Inf. Sci. 369: 199-220 (2016) - 2015
- [j2]Yuan-Hai Shao, Xiang-Yu Hua, Li-Ming Liu, Zhi-Min Yang, Nai-Yang Deng:
Combined outputs framework for twin support vector machines. Appl. Intell. 43(2): 424-438 (2015) - [j1]Yuan-Hai Shao, Wei-Jie Chen, Li-Ming Liu, Nai-Yang Deng:
Laplacian unit-hyperplane learning from positive and unlabeled examples. Inf. Sci. 314: 152-168 (2015)
Coauthor Index
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