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Mingzhen He
Mingzhen He
在 sjtu.edu.cn 的电子邮件经过验证
标题
引用次数
引用次数
年份
Learning with asymmetric kernels: Least squares and feature interpretation
M He, F He, L Shi, X Huang, JAK Suykens
IEEE Transactions on Pattern Analysis and Machine Intelligence 45 (8), 10044 …, 2023
92023
Runge–Kutta type discrete circadian RNN for resolving tri-criteria optimization scheme of noises perturbed redundant robot manipulators
Z Zhang, X Deng, M He, T Chen, J Liang
IEEE Transactions on Systems, Man, and Cybernetics: Systems 52 (3), 1405-1416, 2020
92020
Learning non-parametric kernel via matrix decomposition for logistic regression
K Wang, F He, M He, X Huang
Pattern Recognition Letters 171, 177-183, 2023
22023
Taylor discrete circadian rhythms neural network for resolving bicriteria optimization problem of redundant robot manipulators perturbed by periodic noises
Z Zhang, S Chen, M He
IEEE Transactions on Industrial Informatics 18 (9), 6015-6025, 2021
22021
Enhancing Kernel Flexibility via Learning Asymmetric Locally-Adaptive Kernels
F He, M He, L Shi, X Huang, JAK Suykens
arXiv preprint arXiv:2310.05236, 2023
12023
Learning Analysis of Kernel Ridgeless Regression with Asymmetric Kernel Learning
F He, M He, L Shi, X Huang, JAK Suykens
arXiv preprint arXiv:2406.01435, 2024
2024
Data Imputation by Pursuing Better Classification: A Supervised Kernel-Based Method
R Yang, F He, M He, K Wang, X Huang
arXiv preprint arXiv:2405.07800, 2024
2024
Decentralized Kernel Ridge Regression Based on Data-dependent Random Feature
R Yang, F He, M He, J Yang, X Huang
arXiv preprint arXiv:2405.07791, 2024
2024
Diffusion representation for asymmetric kernels via magnetic transform
M He, F He, R Yang, X Huang
Advances in Neural Information Processing Systems 36, 2024
2024
Random Fourier Features for Asymmetric Kernels
M He, F He, F Liu, X Huang
arXiv preprint arXiv:2209.08461, 2022
2022
Global Search and Analysis for the Nonconvex Two-Level ℓ₁ Penalty
F He, M He, L Shi, X Huang
IEEE Transactions on Neural Networks and Learning Systems 35 (3), 3886-3899, 2022
2022
Data Imputation by Pursuing Better Classification: A Supervised Learning Approach
R Yang, FAN He, M He, K Wang
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