简介


杨晶华，西南交通大学信息科学与技术学院讲师。博士就读于澳门科技大学资讯科技学院，人工智能专业，导师为戴宏宁教授和陈川副教授。 硕士就读于电子科技大学数学科学学院，计算数学专业。目前研究方向包括数据挖掘，图像处理、张量分析，深度学习，联邦学习等。

邮箱: yangjinghua110@126.com
链接: Google Scholar  

消息

  • 2022.10: 文章 J-H. Yang, C. Chen, H-N. Dai, M. Ding, Z. Wu, Z. Zheng [“Robust Corrupted Data Recovery and Clustering via Generalized Transformed Tensor Low-rank Representation”] 被期刊 IEEE Transactions on Neural Networks and Learning Systems 接受.
  • 2022.10: 文章 J-H. Yang, L-L. Fu, C. Chen, H-N. Dai, Z. Zheng [“Cross-View Graph Matching for Incomplete Multi-view Clustering”] 被期刊 Neurocomputing 接受.
  • 2022.8: 文章 J-H. Yang, C. Chen, H-N. Dai, L-L. Fu, Z. Zheng [“A structure noise-aware tensor dictionary learning method for high-dimensional data clustering”] 被期刊 Information Sciences 接受.
  • 2022.8: 文章 J-H. Yang, C. Chen, H-N. Dai, M. Ding, L-L. Fu, Z. Zheng [“Hierarchical representation for multi-view clustering: from intra-sample to intra-view to inter-view”] 被会议 CIKM2022 接受.
  • 2021.12: 文章 X-L. Zhao, J-H. Yang, T-H. Ma, T-X Jiang, M. K. Ng, T-Z. Huang [“Tensor completion via complementary global, local, and nonlocal priors”] 被期刊 IEEE Transactions on Image Processing 接受.
  • 2020.01: 文章 J-H. Yang, X-L. Zhao, T-H. Ma, M. Ding, T-Z. Huang “Tensor train rank minimization with hybrid smoothness regularization for visual data recovery” 被期刊 Applied Mathematical Modelling 接受.

学术论文

期刊 (发表)

  • Jing-Hua Yang, Chuan Chen, Hong-Ning Dai, Meng Ding, Zhebin Wu, Zibin Zheng, “Robust Corrupted Data Recovery and Clustering via Generalized Transformed Tensor Low-rank Representation”, IEEE Transactions on Neural Networks and Learning Systems, 2022. [全文]

  • Jing-Hua Yang, Le-Le Fu, Chuan Chen, Hong-Ning Dai, Zibin Zheng, “Cross-View Graph Matching for Incomplete Multi-view Clustering”, Neurocomputing, vol. 515, pp. 79-88, 2023. [全文]

  • Jing-Hua Yang, Chuan Chen, Hong-Ning Dai, Le-Le Fu, Zibin Zheng, “A structure noise-aware tensor dictionary learning method for high-dimensional data clustering”, Information Sciences, vol. 612, pp. 87-106, 2022. [全文]

  • Le-Le Fu, Jing-Hua Yang, Chuan Chen, Chuan-fu Zhang, “Low-rank tensor approximation with local structure for multi-view intrinsic subspace clustering”, Information Sciences, vol. 606, pp. 877-891, 2022. [全文]

  • Xi-Le Zhao, Jing-Hua Yang, Tian-Hui Ma, Tai-Xiang Jiang, Michael K. Ng，Ting-Zhu Huang, “Tensor completion via complementary global, local, and nonlocal priors”, IEEE Transactions on Image Processing, vol. 31, pp. 984-999, 2021. [全文]

  • Jing-Hua Yang, Xi-Le Zhao, Tian-Hui Ma, Meng Ding, Ting-Zhu Huang, “Tensor train rank minimization with hybrid smoothness regularization for visual data recovery”, Applied Mathematical Modelling, vol. 81, pp. 711-726, 2020. [全文]

  • Jing-Hua Yang, Xi-Le Zhao, Teng-Yu Ji, Tian-Hui Ma, Ting-Zhu Huang, “Low-rank tensor train for tensor robust principal component analysis”, Journal of Applied Mathematics and Computation, vol. 367, pp. 124783, 2020. [全文]

  • Jing-Hua Yang, Xi-Le Zhao, Tian-Hui Ma, Yong Chen, Ting-Zhu Huang, Meng Ding, “Remote sensing images destriping using unidirectional hybrid total variation and nonconvex low-rank regularization”, Journal of Computational and Applied Mathematics, vol. 363, pp. 124-144, 2020. [全文]

  • Jing-Hua Yang, Xi-Le Zhao, Tian-Hui Ma, Yong Chen, Ting-Zhu Huang, Meng Ding, “Total variation and high-order total variation adaptive model for restoring blurred images with Cauchy noise”, Journal of Computers and Mathematics with Applications, vol. 77, pp. 1255-1272, 2019. [全文]

  • Meng Ding, Ting-Zhu Huang, Tian-Hui Ma, Xi-Le Zhao, Jing-Hua Yang, “Cauchy noise removal using group-based low-rank prior”, Applied Mathematics and Computation, vol. 372, pp. 124971, 2020. [[全文] (https://MengDing56.gitHub.io/papers/20AMC_Nonlocal_Cauchy.pdf) [代码]

  • Meng Ding, Ting-Zhu Huang, Teng-Yu Ji, Xi-Le Zhao, Jing-Hua Yang, “Low-Rank Tensor Completion Using Matrix Factorization Based on Tensor Train Rank and Total Variation”, Journal of Scientific Computing, vol. 81, pp. 941–964, 2020. [全文] [代码]

会议 (发表)

  • Jing-Hua Yang, Chuan Chen, Hong-Ning Dai, Meng Ding, Le-le Fu, Zibin Zheng, “Hierarchical representation for multi-view clustering: from intra-sample to intra-view to inter-view”, In ACM International Conference on Information and Knowledge Management, 2022. [全文]

  • Meng Ding, Ting-Zhu Huang, Xi-Le Zhao, Jie Lin, Jing-Hua Yang, “Factor-regularized nonnegative tensor decomposition for blind hyperspectral unmixing”, In IEEE International Geoscience and Remote Sensing Symposium IGARSS, 2021. [全文]

教育背景

  • 09/2020-至今: 博士, 澳门科技大学 人工智能专业 (导师: 戴弘宁教授)

  • 09/2019-06/2020: 助教, 电子科技大学成都学院

  • 09/2016-06/2019: 硕士, 电子科技大学 数学专业 (导师: 赵熙乐教授)

  • 09/2012-06/2016: 本科, 太原师范学院 数学与应用数学专业

获奖情况

  • 参与学术研究助学金 (PGS) 澳门科技大学 2020-2023

  • 一等学业奖学金 电子科技大学 2018

  • 一等学业奖学金 电子科技大学 2017