| 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 | 13 | 2023 |
| 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 | 10 | 2020 |
| Decentralized kernel ridge regression based on data-dependent random feature R Yang, F He, M He, J Yang, X Huang IEEE transactions on neural networks and learning systems, 2024 | 3 | 2024 |
| 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 | 3 | 2023 |
| 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 | 3 | 2021 |
| Random fourier features for asymmetric kernels M He, F He, F Liu, X Huang Machine Learning 113 (11), 8459-8485, 2024 | 2 | 2024 |
| MUSO: Achieving Exact Machine Unlearning in Over-Parameterized Regimes R Yang, M He, Z He, Y Qiu, X Huang arXiv preprint arXiv:2410.08557, 2024 | 1 | 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 | 1 | 2024 |
| Data imputation by pursuing better classification: a supervised learning approach R Yang, FAN He, M He, K Wang | 1 | 2024 |
| Diffusion representation for asymmetric kernels via magnetic transform M He, F He, R Yang, X Huang Advances in Neural Information Processing Systems 36, 53742-53761, 2023 | 1 | 2023 |
| 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 | 1 | 2023 |
| 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 | 1 | 2022 |
| 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 |
| Primphormer: Leveraging Primal Representation for Graph Transformers M He, R Yang, H Tian, Y Qiu, X Huang | | |
| Simulating Training Dynamics to Reconstruct Training Data from Deep Neural Networks H Tian, Y Liu, M He, Z He, Z Huang, R Yang, X Huang The Thirteenth International Conference on Learning Representations, 0 | | |
Xiaolin Huang (黄晓霖)Professor, Shanghai Jiao Tong Universityכתובת אימייל מאומתת בדומיין sjtu.edu.cn