Scholar
Mingzhen He
Google Scholar ID: bgeZwfQAAAAJ
Shanghai Jiao Tong University
Citations & Impact
Citations
88
H-index
5
i10-index
3
Publications
20
Co-authors
0
Publications
Resume (English only)
Academic Achievements
- May 2025: One paper about efficient graph Transformers via the primal-dual relationship of asymmetric kernels was accepted by ICML. January 2025: One paper was accepted by ICLR. September 2024: One paper was accepted by NeurIPS; another paper on random Fourier features for asymmetric kernels was accepted by Machine Learning. July 2024: One paper was accepted by IEEE Transactions on Neural Networks and Learning Systems. September 2023: One paper about a dimension reduction method for asymmetric kernels was accepted by NeurIPS. July 2023: One paper was accepted by Pattern Recognition Letters. March 2023: One paper was accepted by IEEE Transactions on Pattern Analysis and Machine Intelligence about the primal-dual relationship of asymmetric kernels. August 2022: One paper was accepted by IEEE Transactions on Neural Networks and Learning Systems.
Research Experience
- Engaged in doctoral research work at the Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University.
Education
- Ph.D. degree: Shanghai Jiao Tong University, Department of Automation, supervised by Prof. Xiaolin Huang; Bachelor's degree: South China University of Technology, major in Automation.
Background
- Research Interests: Investigating asymmetric kernels, the primal-dual relationship, and random features. Current research focuses on machine learning theory (potential function space for asymmetric kernels) and applications (Graph Neural Networks and Transformers understood by asymmetric kernels). Brief introduction: Ph.D. student at the Institute of Image Processing Pattern Recognition in the Department of Automation, Shanghai Jiao Tong University.
Miscellany
- Contact: Feel free to drop an email to connect; Social Platforms: GitHub
Co-authors