发表论文
代表作：
1. Yang, Ming, Qilun Luo, Wen Li, and Mingqing Xiao. "3D Array Image Data Completion by Tensor Decomposition and Nonconvex Regularization Approach." IEEE Transactions on Signal Processing, vol. 70, pp. 4291-4304, 2022.
2. Yang, Ming, Qilun Luo, Wen Li, and Mingqing Xiao. "Multiview clustering of images with tensor rank minimization via nonconvex approach." SIAM Journal on Imaging Sciences 13, no. 4 (2020): 2361-2392.
3. Yang Ming, Qilun Luo, Wen Li, and Mingqing Xiao. "Nonconvex 3D array image data recovery and pattern recognition under tensor framework." Pattern Recognition (Elsevier) 122 (2022): 108311.
4. Yang, Ming, Wen Li, and Mingqing Xiao. "On identifiability of higher order block term tensor decompositions of rank Lr⊗ rank-1." Linear and Multilinear Algebra (Taylor & Francis) 68, no. 2 (2020): 223-245.
5. Quan Yu and Ming Yang* (通讯)"Low Rank Tensor Recovery via Non-convex Regularization, Structured
Factorization and Spatio-Temporal Characteristics” Pattern Recognition (Elsevier) (2023): 109343
其他：
1. Tingquan Deng; Jingyu Wang; Qingwei Jia; Ming Yang, Semi-supervised sparse representation collaborative clustering of incomplete data. Appl Intell 53, 31077–31105 (2023)
2. Zhou, Qian, Qianqian Wang, Quanxue Gao, Ming Yang, and Xinbo Gao. "Unsupervised Discriminative Feature Selection via Contrastive Graph Learning." IEEE Transactions on Image Processing (2024).
3. Li, Jing, Quanxue Gao, Qianqian Wang, Ming Yang, and Wei Xia, Orthogonal Non-negative Tensor Factorization based Multi-view Clustering. In Proceedings of the 37th Conference on Neural Information Processing Systems (NeurIPS 2023). 2023.
4. Li, Jing, Quanxue Gao, Qianqian Wang, Ming Yang, and Xinbo Gao, Efficient Anchor Graph Factorization for Multi-view Clustering. IEEE Transactions on Multimedia. 2023.
5. Lu, Han, Huafu Xu, Qianqian Wang, Quanxue Gao, Ming Yang and Xinbo Gao, Efficient Multi-View K-Means for Image Clustering. IEEE Transactions on Image Processing, 2023.
6. Luo, Qilun, Ming Yang, Wen Li, and Mingqing Xiao. "Hyper-Laplacian Regularized Multi-View Clustering with Exclusive L21 Regularization and Tensor Log-Determinant Minimization Approach." ACM Transactions on Intelligent Systems and Technology 14, no. 3 (2023): 1-29.
7. Deng, Tingquan, Ge Yang, Yang Huang, Ming Yang, and Hamido Fujita. "Adaptive multi-granularity sparse subspace clustering." Information Sciences 642 (2023): 119143.
8. Qilun Luo, Ming Yang, Wen Li, and Mingqing Xiao. "Multi-Dimensional Data Processing with Bayesian Inference via Structural Block Decomposition." IEEE Transactions on Cybernetics (2023).
9. Xie, Deyan, Quanxue Gao, and Ming Yang. "Enhanced tensor low-rank representation learning for multi-view clustering." Neural Networks 161 (2023): 93-104.
10. Mei, Shikun, Wenhui Zhao, Quanxue Gao, Ming Yang, and Xinbo Gao. "Joint feature selection and optimal bipartite graph learning for subspace clustering." Neural Networks 164 (2023): 408-418.
11. Yun, Yu, Jing Li, Quanxue Gao, Ming Yang, and Xinbo Gao. "Low-rank discrete multi-view spectral clustering." Neural Networks 166 (2023): 137-147.
12. Zhou, Qian, Quanxue Gao, Qianqian Wang, Ming Yang, and Xinbo Gao. "Sparse discriminant PCA based on contrastive learning and class-specificity distribution." Neural Networks 167 (2023): 775-786.
13. Li, Guangfei, Quanxue Gao, Ming Yang, and Xinbo Gao. "Active learning based on similarity level histogram and adaptive-scale sampling for very high resolution image classification." Neural Networks 167 (2023): 22-35.
14. Zhao, Wenhui, Quanxue Gao, Shikun Mei, and Ming Yang. "Contrastive self-representation learning for data clustering." Neural Networks 167 (2023): 648-655.
15. Xia, Wei, Tianxiu Wang, Quanxue Gao, Ming Yang, and Xinbo Gao. "Graph embedding contrastive multi-modal representation learning for clustering." IEEE Transactions on Image Processing 32 (2023): 1170-1183.
16. Xia, Wei, Quanxue Gao, Xinbo Gao, Ming Yang. " Self-consistent Contrastive Attributed Graph Clustering with Pseudo-label Prompt” IEEE Transactions on Multimedia (2022).
17. Shu, Xiaochuang, Quanxue Gao, Wei Xia, Ming Yang, and Xinbo Gao. "Self-weighted anchor graph learning for multi-view clustering.” IEEE Transactions on Multimedia (2022).
18. Sun, Xiaoli, Youjuan Wang, Ming Yang, and Xiujun Zhang. "Sliced sparse gradient induced multi-view subspace clustering via tensorial arctangent rank minimization." IEEE Transactions on Knowledge and Data Engineering. 2022 Jun 21.
19. Lv, Ziyu, Quanxue Gao, Xiangdong Zhang, Qin Li, and Ming Yang "View-consistency learning for incomplete multi-view clustering.” IEEE Transactions on Image Processing, vol. 31, pp. 4790-4802, 2022
20. Yang, Haizhou, Quanxue Gao, Wei Xia, Ming Yang, and Xinbo Gao. "Multi-view Spectral Clustering with Bipartite Graph." IEEE Transactions on Image Processing, vol. 31, pp. 3591-3605, 2022
21. Li, Qin, Mingzhen Hou, Hong Lai, Ming Yang. "Cross-modal Distribution Alignment Embedding Network for Generalized Zero-shot Learning." Neural Networks (Elsevier) 146 (2022)
22. Xia, Wei, Sen Wang, Ming Yang, Quanxue Gao, Jungong Han, and Xinbo Gao. "Multi-view graph embedding clustering network: Joint self-supervision and block diagonal representation." Neural Networks (Elsevier) 145 (2022): 1-9.
23. Cai, Shuting, Qilun Luo, Ming Yang*, Wen Li, and Mingqing Xiao*. "Tensor robust principal component analysis via non-convex low rank approximation." Applied Sciences (MDPI) 9, no. 7 (2019).
24. Cai, Shuting, Kun Liu, Ming Yang*, Jianliang Tang, Xiaoming Xiong, and Mingqing Xiao. "A new development of non-local image denoising using fixed-point iteration for non-convex ？p sparse optimization." PloS one 13, no. 12 (2018): e0208503.
25. Peng, Chong, Zhao Kang, Ming Yang, and Qiang Cheng. "Feature selection embedded subspace clustering." IEEE Signal Processing Letters 23, no. 7 (2016): 1018-1022.
26. Yang, Ming. "On partial and generic uniqueness of block term tensor decompositions." Annali dell' Università di Ferrara (Springer) 60, no. 2 (2014): 465-493.
27. Foias, Ciprian, M. S. Jolly, and Ming Yang. "On single mode forcing of the 2D-NSE." Journal of Dynamics and Differential Equations (Springer) 25, no. 2 (2013): 393-433.
28. Lu, Han, Quanxue Gao, Qianqian Wang, Ming Yang, and Wei Xia. "Centerless multi-view K-means based on the adjacency matrix." In Proceedings of the AAAI Conference on Artificial Intelligence, vol. 37, no. 7, pp. 8949-8956. 2023.
29. Peng, Chong, Zhao Kang, Ming Yang, and Qiang Cheng. "RAP: Scalable RPCA for low-rank matrix recovery." In Proceedings of the 25th ACM International Conference on Information and Knowledge Management, pp. 2113-2118. 2016.
30. Kang, Zhao, Chong Peng, Ming Yang, and Qiang Cheng. "Top-n recommendation on graphs." In Proceedings of the 25th ACM International Conference on Information and Knowledge Management, pp. 2101-2106. 2016.
31. Kang, Zhao, Chong Peng, Ming Yang, and Qiang Cheng. "Exploiting nonlinear relationships for top-n recommender systems." In 2017 IEEE International Conference on Big Knowledge (ICBK), pp. 49-56. IEEE, 2017.
32. Yang, Ming, Dunren Che, Wen Liu, Zhao Kang, Chong Peng, Mingqing Xiao, and Qiang Cheng. "On identifiability of 3-tensors of multilinear rank (1,Lr,Lr) ." Big Data and Information Analytics (BDIA), American Institute of Mathematical Sciences, Vol. 1, no. 4, October 2016.
