JOURNAL PAPERS

  1. H Zhang, L Liu, F Hui, B Zhang, Hengmin Zhang, and Z Zha. CLEAN: Category Knowledge-Driven Compression Framework for Efficient 3D Object Detection[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2025, 47(10): 8740-8755.  Code
  2. Hengmin Zhang, J Yang, W Du, B Zhang, Z Zha, and B Wen. Enhanced Acceleration for Generalized Nonconvex Low-rank Matrix Learning[J]. Chinese Journal of Electronics, 2025, 34(1), 98-113.
  3. Hengmin Zhang, J Zhao, B Zhang, C Gong, J Qian, and J Yang. Unified Framework for Faster Clustering via Joint Schatten p-norm Factorization with Optimal Mean[J]. IEEE Transactions on Neural Networks and Learning Systems, 2024, 35 (3), 3012-3026.  Code
  4. Hengmin Zhang, J Yang, J Qian, C Gong, X Ning, Z Zha, and B Wen. Faster Nonconvex Low-rank Matrix Learning for Image Low-level and High-level Vision: A Unified Framework[J]. Information Fusion, 108: 102347.  Code
  5. Hengmin Zhang, J Yang, J Qian, G Gao, X Lan, Z Zha, and B Wen. Efficient Image Classification via Structured Low-rank Matrix Factorization Regression[J]. IEEE Transactions on Information Forensics and Security, 2024, 19, 1496-1509.  Code
  6. Hengmin Zhang, B Wen, Z Zha, B Zhang, Y Tang, G Yu, and W Du. Accelerated PALM for Nonconvex Low-rank Matrix Recovery with Theoretical Analysis[J]. IEEE Transactions on Circuits and Systems for Video Technology, 2024, 34 (4), 2304-2317.  Code
  7. Hengmin Zhang, J Gao, J Qian, J Yang, C Xu, and B Zhang. Linear Regression Problem Relaxations Optimized by Nonconvex ADMM with Convergence Analysis[J]. IEEE Transactions on Circuits and Systems for Video Technology, 2024, 34 (2), 828-838.  Code
  8. Hengmin Zhang, J Yang, B Zhang, Y Tang, W Du, and B Wen. Enhancing Generalized Spectral Clustering with Embedding Laplacian Graph Regularization[J]. CAAI Transactions on Intelligence Technology, 2024, 1-18.  Code
  9. M Liu, S Lin, Hengmin Zhang, Z Zha, and B Wen. Intrinsic-style Distribution Matching for Arbitrary Style Transfer[J]. Knowledge-Based Systems, 2024, 296: 111898.
  10. J Zhou, Hengmin Zhang, S Li, B Zhang, L Fang, and D Zhang. Dual Low-rank Structure Embedding for Robust Visual Information Processing[J]. Knowledge-Based Systems, 2024, 296: 111821.
  11. Hengmin Zhang, F Qian, P Shi, W Du, Y Tang, J Qian, C Gong, and J Yang. Generalized Nonconvex Nonsmooth Low-rank Matrix Recovery Framework with Feasible Algorithm Designs and Convergence Analysis[J]. IEEE Transactions on Neural Networks and Learning Systems, 2023, 34(9): 5342-5353.
  12. Hengmin Zhang, S Li, J Qiu, Y Tang, J Wen, Z Zha, and B Wen. Efficient and Effective Nonconvex Low-rank Subspace Clustering via SVT-free Operators[J]. IEEE Transactions on Circuits and Systems for Video Technology, 2023, 33 (12), 7515-7529.
  13. S Li, Hengmin Zhang, R Ma, J Zhou, J Wen, and B Zhang. Linear Discriminant Analysis with Generalized Kernel Constraint for Robust Image Classification[J]. Pattern Recognition, 2023, 109196.
  14. Hengmin Zhang, F Qian, B Zhang, W Du, J Qian, and J Yang. Incorporating Linear Regression Problems Into An Adaptive Framework with Feasible Optimizations[J]. IEEE Transactions on Multimedia, 2023, 25: 4041-4051.
  15. G Yu, L Ma, Y Jin, W Du, Q Liu, and Hengmin Zhang. A Survey on Knee-oriented Multi-objective Evolutionary Optimization[J]. IEEE Transactions on Evolutionary Computation, 2022, 26(6): 1452-1472.
  16. J Qian, W Wong, Hengmin Zhang, J Xie, and J Yang. Joint Optimal Transport with Convex Regularization for Robust Image Classification[J]. IEEE Transactions on Cybernetics, 2022, 52(3): 1553-1564.
  17. Hengmin Zhang, F Qian, F Shang, W Du, J Qian, and J Yang. Global Convergence Guarantees of (A)GIST for a Family of Noncovex Sparse Learning Problems[J]. IEEE Transactions on Cybernetics, 2022, 52(5): 3276-3288.
  18. J Qian, S Zhu, W Wong, Hengmin Zhang, Z Lai, and J Yang. Dual Robust Regression for Pattern Classification[J]. Information Sciences, 2021, 546: 1014-1029.
  19. Hengmin Zhang, J Qian, B Zhang, J Yang, C Gong, and Y Wei. Low-rank Matrix Recovery via Modified Schatten-p Norm Minimization with Convergence Guarantees[J]. IEEE Transactions on Image Processing, 2020, 29, 3132-3142.
  20. Hengmin Zhang, J Yang, F Shang, C Gong, and Z Zhang. LRR for Subspace Segmentation via Tractable Schatten-p Norm Minimization and Factorization[J]. IEEE Transactions on Cybernetics, 2019, 49(5): 1722-1734.
  21. Hengmin Zhang, C Gong, J Qian, B Zhang, C Xu, and J Yang. Efficient Recovery of Low Rank Matrix via Double Nonconvex Nonsmooth Rank Minimization[J]. IEEE Transactions on Neural Networks and Learning Systems, 2019, 30(10): 2916-2925.
  22. Hengmin Zhang, J Qian, J Gao, J Yang, and C Xu. Scalable Proximal Jacobian Iteration Method with Global Convergence Analysis for Nonconvex Unconstrained Composite Optimizations[J]. IEEE Transactions on Neural Networks and Learning Systems, 2019, 30(9), 2825-2839.
  23. 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.
  24. J Xie, J Yang, J Qian, Y Tai, and Hengmin Zhang. Robust Nuclear Norm-Based Matrix Regression With Applications to Robust Face Recognition[J]. IEEE Transactions on Image Processing, 2017, 26(5): 2286-2295.
  25. Hengmin Zhang, J Yang, J Xie, J Qian, and B Zhang. Weighted Sparse Coding Regularized Nonconvex Matrix Regression for Robust Face Recognition[J]. Information Sciences, 2017, 394: 1-17.
  26. Y Chen, J Yang, L Luo, Hengmin Zhang, J Qian, Y Tai, and J Zhang. Adaptive Noise Dictionary Construction via IRRPCA for Face Recognition[J]. Pattern Recognition, 2016, 59: 26-41.