Követés
Shixiang Chen
Cím
Hivatkozott rá
Hivatkozott rá
Év
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
144*2020
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
73*2021
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
672022
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
422022
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
39*2020
Decentralized Riemannian Gradient Descent on the Stiefel Manifold
S Chen, A Garcia, M Hong, S Shahrampour
International Conference on Machine Learning, 2021
332021
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
30*2021
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
222021
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
182024
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
162022
Geometric descent method for convex composite minimization
S Chen, S Ma, W Liu
Advances in Neural Information Processing Systems, 636-644, 2017
152017
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
142024
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
122023
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
92019
Decentralized Weakly Convex Optimization Over the Stiefel Manifold
J Wang, J Hu, S Chen, Z Deng, AMC So
arXiv preprint arXiv:2303.17779, 2023
52023
Nonconvex Robust Synchronization of Rotations
H Liu, Z Deng, X Li, S Chen, AMC So
NeurIPS Workshop on Optimization for Machine Learning, 0
5*
First-Order Algorithms for Structured Optimization: Convergence, Complexity and Applications
S Chen
The Chinese University of Hong Kong (Hong Kong), 2019
22019
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
2024
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
2024
Decentralized Non-Smooth Optimization Over the Stiefel Manifold
J Wang, J Hu, S Chen, Z Deng, AMC So
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