Taylor Discrete Circadian Rhythms Neural Network for Resolving Bicriteria Optimization Problem of Redundant Robot Manipulators Perturbed by Periodic Noises. - Zhijun Zhang 003; Siyuan Chen 006; Mingzhen He (IEEE Trans. Ind. Informatics, 2022)

Runge-Kutta Type Discrete Circadian RNN for Resolving Tri-Criteria Optimization Scheme of Noises Perturbed Redundant Robot Manipulators. - Zhijun Zhang 003; Xianzhi Deng; Mingzhen He; Tao Chen 025; Junjie Liang (IEEE Trans. Syst. Man Cybern. Syst., 2022)

Diffusion Representation for Asymmetric Kernels via Magnetic Transform. - Mingzhen He; Fan He; Ruikai Yang; Xiaolin Huang (NeurIPS, 2023)

Enhancing Kernel Flexibility via Learning Asymmetric Locally-Adaptive Kernels. - Fan He; Mingzhen He; Lei Shi 010; Xiaolin Huang; Johan A. K. Suykens (CoRR, 2023)

Learning non-parametric kernel via matrix decomposition for logistic regression. - Kaijie Wang; Fan He; Mingzhen He; Xiaolin Huang (Pattern Recognit. Lett., 2023)

Learning With Asymmetric Kernels: Least Squares and Feature Interpretation. - Mingzhen He; Fan He; Lei Shi 010; Xiaolin Huang; Johan A. K. Suykens (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Kernel PCA for Out-of-Distribution Detection. - Kun Fang 004; Qinghua Tao; Kexin Lv; Mingzhen He; Xiaolin Huang; Jie Yang 002 (NeurIPS, 2024)

Data Imputation by Pursuing Better Classification: A Supervised Kernel-Based Method. - Ruikai Yang; Fan He; Mingzhen He; Kaijie Wang; Xiaolin Huang (CoRR, 2024)

Learning Analysis of Kernel Ridgeless Regression with Asymmetric Kernel Learning. - Fan He; Mingzhen He; Lei Shi 010; Xiaolin Huang; Johan A. K. Suykens (CoRR, 2024)

MUSO: Achieving Exact Machine Unlearning in Over-Parameterized Regimes. - Ruikai Yang; Mingzhen He; Zhengbao He; Youmei Qiu; Xiaolin Huang (CoRR, 2024)

Revisiting Random Weight Perturbation for Efficiently Improving Generalization. - Tao Li 054; Qinghua Tao; Weihao Yan; Yingwen Wu; Zehao Lei; Kun Fang 004; Mingzhen He; Xiaolin Huang (Trans. Mach. Learn. Res., 2024)

Global Search and Analysis for the Nonconvex Two-Level ℓ₁ Penalty. - Fan He; Mingzhen He; Lei Shi 010; Xiaolin Huang (IEEE Trans. Neural Networks Learn. Syst., 2024)

Random fourier features for asymmetric kernels. - Mingzhen He; Fan He; Fanghui Liu 001; Xiaolin Huang (Mach. Learn., 2024)

Simulating Training Dynamics to Reconstruct Training Data from Deep Neural Networks. - Hanling Tian; Yuhang Liu 003; Mingzhen He; Zhengbao He; Zhehao Huang; Ruikai Yang; Xiaolin Huang (ICLR, 2025)

Kernel PCA for Out-of-Distribution Detection: Non-Linear Kernel Selections and Approximations. - Kun Fang 004; Qinghua Tao; Mingzhen He; Kexin Lv; Runze Yang; Haibo Hu; Xiaolin Huang; Jie Yang 002; Longbing Cao (CoRR, 2025)

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training. - Zhehao Huang; Yuhang Liu 003; Yixin Lou; Zhengbao He; Mingzhen He; Wenxing Zhou; Tao Li; Kehan Li; Zeyi Huang; Xiaolin Huang (CoRR, 2025)

Decentralized Kernel Ridge Regression Based on Data-Dependent Random Feature. - Ruikai Yang; Fan He; Mingzhen He; Jie Yang 002; Xiaolin Huang (IEEE Trans. Neural Networks Learn. Syst., 2025)

MUSO: achieving exact machine unlearning in over-parameterized regimes. - Ruikai Yang; Mingzhen He; Zhenghao He; Youmei Qiu; Xiaolin Huang (Mach. Learn., 2025)