| Proximal gradient method for nonsmooth optimization over the Stiefel manifold S Chen, S Ma, A Man-Cho So, T Zhang SIAM Journal on Optimization 30 (1), 210-239, 2020 | 177 | 2020 |
| Inducing Neural Collapse in Imbalanced Learning: Do We Really Need a Learnable Classifier at the End of Deep Neural Network? Y Yang, S Chen, X Li, L Xie, Z Lin, D Tao NeurIPS 2022, 2022 | 127 | 2022 |
| Weakly convex optimization over Stiefel manifold using Riemannian subgradient-type methods X Li, S Chen, Z Deng, Q Qu, Z Zhu, A Man-Cho So SIAM Journal on Optimization 31 (3), 1605-1634, 2021 | 96* | 2021 |
| Penalized Proximal Policy Optimization for Safe Reinforcement Learning L Zhang, L Shen, L Yang, S Chen, B Yuan, X Wang, D Tao IJCAI 2022, 2022 | 80 | 2022 |
| Dynamic Regularized Sharpness Aware Minimization in Federated Learning: Approaching Global Consistency and Smooth Landscape Y Sun, L Shen, S Chen, L Ding, D Tao ICML 2023, 2023 | 46 | 2023 |
| An alternating manifold proximal gradient method for sparse principal component analysis and sparse canonical correlation analysis S Chen, S Ma, L Xue, H Zou INFORMS Journal on Optimization 2 (3), 192-208, 2020 | 45* | 2020 |
| On distributed nonconvex optimization: Projected subgradient method for weakly convex problems in networks S Chen, A Garcia, S Shahrampour IEEE Transactions on Automatic Control 67 (2), 662-675, 2021 | 44 | 2021 |
| Decentralized Riemannian Gradient Descent on the Stiefel Manifold S Chen, A Garcia, M Hong, S Shahrampour International Conference on Machine Learning, 2021 | 43 | 2021 |
| Adasam: Boosting sharpness-aware minimization with adaptive learning rate and momentum for training deep neural networks H Sun, L Shen, Q Zhong, L Ding, S Chen, J Sun, J Li, G Sun, D Tao Neural Networks 169, 506-519, 2024 | 37 | 2024 |
| Manifold proximal point algorithms for dual principal component pursuit and orthogonal dictionary learning S Chen, Z Deng, S Ma, AMC So IEEE Transactions on Signal Processing, 2021 | 26 | 2021 |
| A manifold proximal linear method for sparse spectral clustering with application to single-cell RNA sequencing data analysis Z Wang, B Liu, S Chen, S Ma, L Xue, H Zhao INFORMS Journal on Optimization 4 (2), 200-214, 2022 | 24 | 2022 |
| Geometric descent method for convex composite minimization S Chen, S Ma, W Liu Advances in Neural Information Processing Systems, 636-644, 2017 | 17 | 2017 |
| On the local linear rate of consensus on the stiefel manifold S Chen, A Garcia, M Hong, S Shahrampour IEEE Transactions on Automatic Control 69 (4), 2324 - 2339, 2024 | 16 | 2024 |
| Manifold proximal point algorithms for dual principal component pursuit and orthogonal dictionary learning S Chen, Z Deng, S Ma, AMC So 2019 53rd Asilomar Conference on Signals, Systems, and Computers, 259-263, 2019 | 9 | 2019 |
| Decentralized Weakly Convex Optimization Over the Stiefel Manifold J Wang, J Hu, S Chen, Z Deng, AMC So arXiv preprint arXiv:2303.17779, 2023 | 7 | 2023 |
| Nonsmooth Optimization over the Stiefel Manifold and Beyond: Proximal Gradient Method and Recent Variants S Chen, S Ma, A Man-Cho So, T Zhang SIAM Review 66 (2), 319-352, 2024 | 6 | 2024 |
| Nonconvex Robust Synchronization of Rotations H Liu, Z Deng, X Li, S Chen, AMC So NeurIPS Workshop on Optimization for Machine Learning, 0 | 5* | |
| Global Convergence of Decentralized Retraction-Free Optimization on the Stiefel Manifold Y Sun, S Chen, A Garcia, S Shahrampour arXiv preprint arXiv:2405.11590, 2024 | 4 | 2024 |
| First-Order Algorithms for Structured Optimization: Convergence, Complexity and Applications S Chen The Chinese University of Hong Kong (Hong Kong), 2019 | 2 | 2019 |
| Local Linear Convergence of Infeasible Optimization With Orthogonal Constraints Y Sun, S Chen, A Garcia, S Shahrampour IEEE Control Systems Letters, 2024 | | 2024 |
Anthony Man-Cho SoDepartment of Systems Engineering and Engineering Management, The Chinese University of Hong Kong確認したメール アドレス: se.cuhk.edu.hk