Mingzhen He

According to our database, Mingzhen He authored at least 18 papers between 2022 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

MUSO: achieving exact machine unlearning in over-parameterized regimes.

Ruikai Yang, Mingzhen He, Zhenghao He, Youmei Qiu, Xiaolin Huang

Mach. Learn., August, 2025

Decentralized Kernel Ridge Regression Based on Data-Dependent Random Feature.

Ruikai Yang, Fan He, Mingzhen He, Jie Yang, Xiaolin Huang

IEEE Trans. Neural Networks Learn. Syst., May, 2025

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training.

Zhehao Huang, Yuhang Liu, Yixin Lou, Zhengbao He, Mingzhen He, Wenxing Zhou, Tao Li, Kehan Li, Zeyi Huang, Xiaolin Huang

CoRR, May, 2025

Kernel PCA for Out-of-Distribution Detection: Non-Linear Kernel Selections and Approximations.

Kun Fang, Qinghua Tao, Mingzhen He, Kexin Lv, Runze Yang, Haibo Hu, Xiaolin Huang, Jie Yang, Longbing Cao

CoRR, May, 2025

Simulating Training Dynamics to Reconstruct Training Data from Deep Neural Networks.

Hanling Tian, Yuhang Liu, Mingzhen He, Zhengbao He, Zhehao Huang, Ruikai Yang, Xiaolin Huang

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

Random fourier features for asymmetric kernels.

Mingzhen He, Fan He, Fanghui Liu, Xiaolin Huang

Mach. Learn., December, 2024

Global Search and Analysis for the Nonconvex Two-Level ℓ₁ Penalty.

Fan He, Mingzhen He, Lei Shi, Xiaolin Huang

IEEE Trans. Neural Networks Learn. Syst., March, 2024

Revisiting Random Weight Perturbation for Efficiently Improving Generalization.

Tao Li, Qinghua Tao, Weihao Yan, Yingwen Wu, Zehao Lei, Kun Fang, Mingzhen He, Xiaolin Huang

Trans. Mach. Learn. Res., 2024

MUSO: Achieving Exact Machine Unlearning in Over-Parameterized Regimes.

Ruikai Yang, Mingzhen He, Zhengbao He, Youmei Qiu, Xiaolin Huang

CoRR, 2024

Learning Analysis of Kernel Ridgeless Regression with Asymmetric Kernel Learning.

Fan He, Mingzhen He, Lei Shi, Xiaolin Huang, Johan A. K. Suykens

CoRR, 2024

Data Imputation by Pursuing Better Classification: A Supervised Kernel-Based Method.

Ruikai Yang, Fan He, Mingzhen He, Kaijie Wang, Xiaolin Huang

CoRR, 2024

Kernel PCA for Out-of-Distribution Detection.

Kun Fang, Qinghua Tao, Kexin Lv, Mingzhen He, Xiaolin Huang, Jie Yang

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

2023

Learning With Asymmetric Kernels: Least Squares and Feature Interpretation.

Mingzhen He, Fan He, Lei Shi, Xiaolin Huang, Johan A. K. Suykens

IEEE Trans. Pattern Anal. Mach. Intell., August, 2023

Learning non-parametric kernel via matrix decomposition for logistic regression.

Kaijie Wang, Fan He, Mingzhen He, Xiaolin Huang

Pattern Recognit. Lett., 2023

Enhancing Kernel Flexibility via Learning Asymmetric Locally-Adaptive Kernels.

Fan He, Mingzhen He, Lei Shi, Xiaolin Huang, Johan A. K. Suykens

CoRR, 2023

Diffusion Representation for Asymmetric Kernels via Magnetic Transform.

Mingzhen He, Fan He, Ruikai Yang, Xiaolin Huang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Runge-Kutta Type Discrete Circadian RNN for Resolving Tri-Criteria Optimization Scheme of Noises Perturbed Redundant Robot Manipulators.

Zhijun Zhang, Xianzhi Deng, Mingzhen He, Tao Chen, Junjie Liang

IEEE Trans. Syst. Man Cybern. Syst., 2022

Taylor Discrete Circadian Rhythms Neural Network for Resolving Bicriteria Optimization Problem of Redundant Robot Manipulators Perturbed by Periodic Noises.

Zhijun Zhang, Siyuan Chen, Mingzhen He

IEEE Trans. Ind. Informatics, 2022