- Dynamic Regularized Sharpness Aware Minimization in Federated Learning: Approaching Global Consistency and Smooth Landscape. Yan Sun, Li Shen, Shixiang Chen, Liang Ding, Dacheng Tao. ICML 2023, Oral.
- Inducing Neural Collapse in Imbalanced Learning: Do We Really Need a Learnable Classifier at the End of Deep Neural Network? Yibo Yang, Shixiang Chen, Liang Xie, Xiangtai Li, Zhouchen Lin, Dacheng Tao. Neurips 2022.
- A Manifold Proximal Linear Method for Sparse Spectral Clustering with Application to Single-Cell RNA Sequencing Data Analysis. Zhongruo Wang，Bingyuan Liu, Shixiang Chen, Shiqian Ma, Lingzhou Xue, Hongyu Zhao. Informs Journal on Optimization.
- Penalized Proximal Policy Optimization for Safe Reinforcement Learning. Linrui Zhang, Li Shen, Long Yang， Shixiang Chen, Bo Yuan , Xueqian Wang , Dacheng Tao. IJCAI 2022.
- Manifold Proximal Point Algorithms for Dual Principal Component Pursuit and Orthogonal Dictionary Learning. Shixiang Chen，Zengde Deng, Shiqian Ma, Anthony Man-Cho So, IEEE Transactions on Signal Processing, 69 (2021): 4759-4773.
- On Distributed Non-convex Optimization: Projected Subgradient Method For Weakly Convex Problems in Networks. Shixiang Chen, Alfredo Garcia and Shahin Shahrampour. IEEE Transactions on Automatic Control, 67 (2021): 662 - 675.
- Decentralized Riemannian Gradient Descent on the Stiefel Manifold. Shixiang Chen, Alfredo Garcia, Mingyi Hong, Shahin Shahrampour. ICML 2021.
- Weakly Convex Optimization over Stiefel Manifold Using Riemannian Subgradient-Type Methods. Xiao Li, Shixiang Chen, Zengde Deng, Qing Qu, Zhihui Zhu and Anthony Man-Cho So. SIAM Journal on Optimization, 31 (3), 1605-1634, 2021..
- An Alternating Manifold Proximal Gradient Method for Sparse PCA and Sparse CCA. Shixiang Chen, Shiqian Ma, Lingzhou Xue and Hui Zou. Informs Journal on Optimization, 2(3):192–208, 2020.
- Geometric descent method for convex composite minimization. Shixiang Chen, Shiqian Ma and Wei Liu. Neurips 2017.