Ganzhao Yuan

Associate Researcher
Peng Cheng Laboratory, Shenzhen City, China

Email: yuanganzhao[at]foxmail[dot]com

Short Biography

My name is Ganzhao Yuan. I was born in a small village in Dongguan City, Guangdong Province, China. I earned my Ph.D. in School of Computer Science and Engineering at South China University of Technology. Previously, I worked as a postdoc researcher in School of Mathematics at South China University of Technology, and in Visual Computing Center at King Abdullah University of Science and Technology. I also worked as a Research Associate Professor in School of Data and Computer Science in Sun Yat-sen University. Currently, I am an Associate Researcher in Peng Cheng Laboratory. My research interests mainly center around mathmatical optimization (e.g., semidefinite optimization, discrete optimization, nonconvex optimization) and its applications (e.g., in machine learning, quantum computing, computer vision).

Selected Publications

  1. Ganzhao Yuan. Smoothing Proximal Gradient Methods for Nonsmooth Sparsity Constrained Optimization: Optimality Conditions and Global Convergence. International Conference on Machine Learning (ICML), 2024.
    [Paper][Code][Poster]

  2. Ganzhao Yuan. Coordinate Descent Methods for Fractional Minimization. International Conference on Machine Learning (ICML), 2023. [CCF A]
    [Paper][Code][Slide]

  3. Ganzhao Yuan. Coordinate Descent Methods for DC Minimization: Optimality Conditions and Global Convergence. Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2023. [CCF A]
    [Paper][Code][Slide][Poster]

  4. Ganzhao Yuan, Li Shen, Wei-Shi Zheng. A Block Decomposition Algorithm for Sparse Optimization. ACM International Conference on Knowledge Discovery and Data Mining (SIGKDD), 2020. [CCF A]
    [Paper][Code][Slide]

  5. Ganzhao Yuan, Li Shen, Wei-Shi Zheng. A Decomposition Algorithm for the Sparse Generalized Eigenvalue Problem. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019. [CCF A]
    [Paper][Code][Slide]

  6. Qing Zhang, Ganzhao Yuan, Chunxia Xiao, Lei Zhu, Wei-Shi Zheng. High-Quality Exposure Correction of Underexposed Photos. ACM Multimedia, 2018. [CCF A]
    [Paper]

  7. Ganzhao Yuan, Bernard Ghanem. L0TV: A Sparse Optimization Method for Impulse Noise Image Restoration. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2018. [CCF A]
    [Paper][Code]

  8. Li Shen, Wei Liu, Ganzhao Yuan, Shiqian Ma. GSOS: Gauss-Seidel Operator Splitting Algorithm for Multi-Term Nonsmooth Convex Composite Optimization. International Conference on Machine Learning (ICML), 2017. [CCF A]
    [Paper]

  9. Ganzhao Yuan, Wei-Shi Zheng, Bernard Ghanem. A Matrix Splitting Method for Composite Function Minimization. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017. [CCF A]
    [Paper][Code][Slide]

  10. Ganzhao Yuan, Bernard Ghanem. An Exact Penalty Method for Binary Optimization Based on MPEC Formulation.Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), pp. 2867-2875, 2017. [CCF A]
    [Paper][Code]

  11. Ganzhao Yuan, Yin Yang, Zhenjie Zhang, Zhifeng Hao. Convex Optimization for Linear Query Processing under Approximate Differential Privacy. ACM International Conference on Knowledge Discovery and Data Mining (SIGKDD), pp. 2005-2014, 2016. [CCF A]
    [Paper] [Code]

  12. Ganzhao Yuan, Bernard Ghanem. A Proximal Alternating Direction Method for Semidefinite Rank Minimization.Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), pp. 2300-2308, 2016. [CCF A]
    [Paper][Code]

  13. Ganzhao Yuan, Zhenjie Zhang, Marianne Winslett, Xiaokui Xiao, Yin Yang, Zhifeng Hao.Optimizing Batch Linear Queries under Exact and Approximate Differential Privacy. ACM Transactions on Database Systems (TODS), 40(2): 11:1-11:47, 2015. [CCF A]
    [Paper][Code]

  14. Ganzhao Yuan, Bernard Ghanem. L0TV: A New Method for Image Restoration in the Presence of Impulse Noise. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 5369-5377, 2015. [Oral, Acc. Rate=71/2151=3.3%, CCF A]
    [Paper][Code][Slide][Abstract]

  15. Ganzhao Yuan, Zhenjie Zhang, Marianne Winslett, Xiaokui Xiao, Yin Yang, Zhifeng Hao. Low-Rank Mechanism: Optimizing Batch Queries under Differential Privacy. International Conference on Very Large Data Bases (VLDB), 5(11):1352-1363, 2012. [CCF A]
    [Paper][Code][Slide]

  16. Ganzhao Yuan, Zhenjie Zhang, Bernard Ghanem, Zhifeng Hao. Low-Rank Quadratic Semidefinite Programming. Neurocomputing, 106(0):51-60, 2013.
    [Paper][Code]

  17. Zhifeng Hao, Ganzhao Yuan, Xiaowei Yang, Zijie Chen. A Primal Method for Multiple Kernel Learning. Neural Computing and Applications 23(3-4):975-987, 2013.
    [Paper][Code]

  18. Zhifeng Hao, Ganzhao Yuan, Bernard Ghanem. BILGO: Bilateral Greedy Optimization for Large Scale Semidefinite Programming. Neurocomputing, 127(0):247-257, 2014.
    [Paper][Code]

Recent Preprints

  1. Ganzhao Yuan. A Block Coordinate Descent Method for Nonsmooth Composite Optimization under Orthogonality Constraints. arXiv preprint, 2023.
    [Paper][Slide]

  2. Ganzhao Yuan. ADMM for Nonconvex Optimization under Minimal Continuity Assumption. arXiv preprint, Jan 2024.
    [Paper]

  3. Ganzhao Yuan. ADMM for Nonsmooth Composite Optimization under Orthogonality Constraints. arXiv preprint, May 2024.
    [Paper]

  4. Di He, Ganzhao Yuan, Xiao Wang, Pengxiang Xu. Block Coordinate Descent Methods for Optimization under J-Orthogonality Constraints with Applications. arXiv preprint, June 2024.
    [Paper]

  5. Ganzhao Yuan. ADMM for Structured Fractional Minimization. arXiv preprint, Dec 2024.
    [Paper]

Unpublished Papers

  1. Ganzhao Yuan, Bernard Ghanem. Sparsity Constrained Minimization via Mathematical Programming with Equilibrium Constraints. arXiv preprint, 2016.
    [Paper]

  2. Ganzhao Yuan, Bernard Ghanem. Binary Optimization via Mathematical Programming with Equilibrium Constraints. arXiv preprint, 2016.
    [Paper]

  3. Ganzhao Yuan, Li Shen, Wei-Shi Zheng. A Hybrid Method of Combinatorial Search and Coordinate Descent for Discrete Optimization. arXiv preprint, 2017.
    [Paper]