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2020 – today
- 2026
[j10]Ruikai Yang
, Fan He, Mingzhen He, Kaijie Wang, Xiaolin Huang:
Data imputation by pursuing better classification: A supervised kernel-based method. Pattern Recognit. 171: 112312 (2026)- 2025
- [j9]Ruikai Yang, Mingzhen He, Zhenghao He, Youmei Qiu, Xiaolin Huang:
MUSO: achieving exact machine unlearning in over-parameterized regimes. Mach. Learn. 114(8): 176 (2025) - [j8]Ruikai Yang, Fan He, Mingzhen He, Jie Yang, Xiaolin Huang:
Decentralized Kernel Ridge Regression Based on Data-Dependent Random Feature. IEEE Trans. Neural Networks Learn. Syst. 36(5): 7945-7954 (2025) - [c4]Hanling Tian, Yuhang Liu, Mingzhen He, Zhengbao He, Zhehao Huang, Ruikai Yang, Xiaolin Huang:
Simulating Training Dynamics to Reconstruct Training Data from Deep Neural Networks. ICLR 2025 - [c3]Mingzhen He, Ruikai Yang, Hanling Tian, Youmei Qiu, Xiaolin Huang:
Primphormer: Efficient Graph Transformers with Primal Representations. ICML 2025 - [i11]Kun Fang, Qinghua Tao, Mingzhen He, Kexin Lv, Runze Yang, Haibo Hu, Xiaolin Huang, Jie Yang, Longbing Cao:
Kernel PCA for Out-of-Distribution Detection: Non-Linear Kernel Selections and Approximations. CoRR abs/2505.15284 (2025) - [i10]Zhehao Huang, Yuhang Liu, Yixin Lou, Zhengbao He, Mingzhen He, Wenxing Zhou, Tao Li, Kehan Li, Zeyi Huang, Xiaolin Huang:
T2I-ConBench: Text-to-Image Benchmark for Continual Post-training. CoRR abs/2505.16875 (2025) - 2024
- [j7]Mingzhen He, Fan He, Fanghui Liu, Xiaolin Huang:
Random fourier features for asymmetric kernels. Mach. Learn. 113(11): 8459-8485 (2024) - [j6]Tao Li, Qinghua Tao, Weihao Yan, Yingwen Wu, Zehao Lei, Kun Fang, Mingzhen He, Xiaolin Huang:
Revisiting Random Weight Perturbation for Efficiently Improving Generalization. Trans. Mach. Learn. Res. 2024 (2024) - [j5]Fan He, Mingzhen He, Lei Shi, Xiaolin Huang:
Global Search and Analysis for the Nonconvex Two-Level ℓ₁ Penalty. IEEE Trans. Neural Networks Learn. Syst. 35(3): 3886-3899 (2024) - [c2]Kun Fang, Qinghua Tao, Kexin Lv, Mingzhen He, Xiaolin Huang, Jie Yang:
Kernel PCA for Out-of-Distribution Detection. NeurIPS 2024 - [i9]Kun Fang, Qinghua Tao, Kexin Lv, Mingzhen He, Xiaolin Huang, Jie Yang:
Kernel PCA for Out-of-Distribution Detection. CoRR abs/2402.02949 (2024) - [i8]Tao Li, Qinghua Tao, Weihao Yan, Zehao Lei, Yingwen Wu, Kun Fang, Mingzhen He, Xiaolin Huang:
Revisiting Random Weight Perturbation for Efficiently Improving Generalization. CoRR abs/2404.00357 (2024) - [i7]Ruikai Yang, Fan He, Mingzhen He, Jie Yang, Xiaolin Huang:
Decentralized Kernel Ridge Regression Based on Data-dependent Random Feature. CoRR abs/2405.07791 (2024) - [i6]Ruikai Yang, Fan He, Mingzhen He, Kaijie Wang, Xiaolin Huang:
Data Imputation by Pursuing Better Classification: A Supervised Kernel-Based Method. CoRR abs/2405.07800 (2024) - [i5]Fan He, Mingzhen He, Lei Shi, Xiaolin Huang, Johan A. K. Suykens:
Learning Analysis of Kernel Ridgeless Regression with Asymmetric Kernel Learning. CoRR abs/2406.01435 (2024) - [i4]Ruikai Yang, Mingzhen He, Zhengbao He, Youmei Qiu, Xiaolin Huang:
MUSO: Achieving Exact Machine Unlearning in Over-Parameterized Regimes. CoRR abs/2410.08557 (2024) - 2023
- [j4]Mingzhen He, Fan He, Lei Shi, Xiaolin Huang, Johan A. K. Suykens:
Learning With Asymmetric Kernels: Least Squares and Feature Interpretation. IEEE Trans. Pattern Anal. Mach. Intell. 45(8): 10044-10054 (2023) - [j3]Kaijie Wang, Fan He, Mingzhen He, Xiaolin Huang:
Learning non-parametric kernel via matrix decomposition for logistic regression. Pattern Recognit. Lett. 171: 177-183 (2023) - [c1]Mingzhen He, Fan He, Ruikai Yang, Xiaolin Huang:
Diffusion Representation for Asymmetric Kernels via Magnetic Transform. NeurIPS 2023 - [i3]Fan He, Mingzhen He, Lei Shi, Xiaolin Huang, Johan A. K. Suykens:
Enhancing Kernel Flexibility via Learning Asymmetric Locally-Adaptive Kernels. CoRR abs/2310.05236 (2023) - 2022
- [j2]Zhijun Zhang, Siyuan Chen, Mingzhen He:
Taylor Discrete Circadian Rhythms Neural Network for Resolving Bicriteria Optimization Problem of Redundant Robot Manipulators Perturbed by Periodic Noises. IEEE Trans. Ind. Informatics 18(9): 6015-6025 (2022) - [j1]Zhijun Zhang, Xianzhi Deng, Mingzhen He, Tao Chen, Junjie Liang:
Runge-Kutta Type Discrete Circadian RNN for Resolving Tri-Criteria Optimization Scheme of Noises Perturbed Redundant Robot Manipulators. IEEE Trans. Syst. Man Cybern. Syst. 52(3): 1405-1416 (2022) - [i2]Mingzhen He, Fan He, Lei Shi, Xiaolin Huang, Johan A. K. Suykens:
Learning with Asymmetric Kernels: Least Squares and Feature Interpretation. CoRR abs/2202.01397 (2022) - [i1]Mingzhen He, Fan He, Fanghui Liu, Xiaolin Huang:
Random Fourier Features for Asymmetric Kernels. CoRR abs/2209.08461 (2022)
Coauthor Index
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