Publications

Please see [Google Scholar] for more my recent work.

Selected Publications:

Notes: The corresponding author is indicated with “*”.

Conference Papers:

[4] Jingjing Zheng, Yuxin Jiang, Wanglong Lu, Lele Wang, Yankai Cao*. Multi-Objective Tensor Recovery via Minimizing Gaussian Complexity. Submitted to CVPR 2025.

[3] Jingjing Zheng, Wanglong Lu, Wenzhe Wang, Yankai Cao*, Xiaoqin Zhang, Xianta Jiang. Handling The Non-Smooth Challenge in Tensor SVD: A Multi-Objective Tensor Recovery Framework. ECCV, 2024. [paper]

[2] Jingjing Zheng, Yankai Cao*. Bayesian-Driven Learning of A New Weighted Tensor Norm for Tensor Recovery. The Second Tiny Papers Track at ICLR, 2024. [paper]

[1] Jingjing Zheng, Xiaoqin Zhang*, Wenzhe Wang, Xianta Jiang. Handling Slice Permutations Variability in Tensor Recovery. AAAI, 2022. [paper][supplementary material][introduction video] [poster]

Journal Papers:

[3] Xiaoqin Zhang, Ziwei Huang, Jingjing Zheng*, Shuo Wang, Xianta Jiang. DcnnGrasp: Towards Accurate Grasp Pattern Recognition with Adaptive Regularizer Learning. SCIENCE CHINA Information Sciences, 2024.

[2] Xiaoqin Zhang*, Jingjing Zheng, Di Wang, Guiying Tang, Zhengyuan Zhou, and Zhouchen Lin. Structured Sparsity Optimization with Non-Convex Surrogates of L2,0-Norm: A Unified Algorithmic Framework. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023. [paper] [code]

[1] Xiaoqin Zhang*, Jingjing Zheng, Li Zhao, Zhengyuan Zhou, Zhouchen Lin. Tensor Recovery with Weighted Tensor Average Rank. IEEE Transactions on Neural Networks and Learning Systems, 2022. [paper] [code]

Dissertations:

[2] Jingjing Zheng. Effective Tensor-Tensor Product-Based Tensor Recovery and Its Efficient Non-Convex Optimization Framework. Memorial University of Newfoundland, 2023. [paper]

[1] Jingjing Zheng. Low rank recovery based on $L_0$ norm non-convex surrogate methods and its application. Wenzhou University, 2020. [paper]