Shixiang Chen

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Preprints

  1. Shixiang Chen, Wen Huang. From Manifold Identification to Newton Acceleration on Intersections: Sparse Stiefel Optimization. 2026. arXiv PDF Code
  2. Dengyu Zheng, Shixiang Chen. A Geometry-Adaptive Regularized Newton-Type Method for Manifold-Affine Intersection Problems. 2026. PDF
  3. Shixiang Chen, Yixiao He, Wen Huang. Retractions by Alternating Projections. 2026. PDF Code
  4. Zisheng Zhou, Dengyu Zheng, Zirui Chen, Shixiang Chen. Descent-Net: Learning Descent Directions for Constrained Optimization. 2025. PDF
  5. Jishu Zhao, Xi Wang, Jinlong Lei, Shixiang Chen. Distributed Stochastic Proximal Algorithm on Riemannian Submanifolds for Weakly-convex Functions. 2025. PDF
  6. Youbang Sun, Shixiang Chen, Alfredo Garcia, Shahin Shahrampour. Global Convergence of Decentralized Retraction-Free Optimization on the Stiefel Manifold. 2024. PDF

Journal papers

  1. Jinxin Wang, Jiang Hu, Shixiang Chen, Anthony Man-Cho So. "Decentralized Weakly Convex Optimization Over the Stiefel Manifold," IEEE Transactions on Signal Processing, 2026. PDF
  2. Shuang Wu, Shixiang Chen, Li Shen, Lefei Zhang, Dacheng Tao. "Constraint Boundary Wandering Framework: Enhancing Constrained Optimization with Deep Neural Networks," IEEE TPAMI, 2025.
  3. Shixiang Chen, Shiqian Ma, Anthony Man-Cho So, and Tong Zhang, "Nonsmooth Optimization over the Stiefel Manifold and Beyond: Proximal Gradient Method and Recent Variants," SIAM Review, 2024. Link (SIGEST paper)
  4. Youbang Sun, Shixiang Chen, Alfredo Garcia, Shahin Shahrampour, "Local Linear Convergence of Infeasible Optimization With Orthogonal Constraints," IEEE Control Systems Letters, 2024. Link
  5. Shixiang Chen, Alfredo Garcia, Mingyi Hong and Shahin Shahrampour. On the Local Linear Rate of Consensus on the Stiefel Manifold. IEEE Transactions on Automatic Control, 2024. Link
  6. Hao Sun, Li Shen, Qihuang Zhong, Liang Ding, Shixiang Chen, Jingwei Sun, Jing Li, Guangzhong Sun, Dacheng Tao. Adasam: Boosting sharpness-aware minimization with adaptive learning rate and momentum for training deep neural networks. Neural Networks, 2024. Link
  7. Zhongruo Wang, Bingyuan Liu, Shixiang Chen, Shiqian Ma, Lingzhou Xue, Hongyu Zhao, "A Manifold Proximal Linear Method for Sparse Spectral Clustering with Application to Single-Cell RNA Sequencing Data Analysis". Informs Journal on Optimization, 2022. Link.
  8. Shixiang Chen, Zengde Deng, Shiqian Ma and Anthony Man-Cho So, "Manifold Proximal Point Algorithms for Dual Principal Component Pursuit and Orthogonal Dictionary Learning", IEEE Transactions on Signal Processing, 2021. Link
  9. Xiao Li*, Shixiang Chen*, Zengde Deng, Qing Qu, Zhihui Zhu, Anthony Man-Cho So, "Weakly Convex Optimization over Stiefel Manifold Using Riemannian Subgradient-Type Methods". SIAM Journal on Optimization, 2021. PDF
  10. Shixiang Chen, Alfredo Garcia and Shahin Shahrampour, "On Distributed Non-convex Optimization: Projected Subgradient Method For Weakly Convex Problems in Networks", IEEE Transactions on Automatic Control, 2021. Link
  11. Shixiang Chen, Shiqian Ma, Lingzhou Xue and Hui Zou, "An Alternating Manifold Proximal Gradient Method for Sparse PCA and Sparse CCA". Informs Journal on Optimization, 2020. Link Code R code
  12. Shixiang Chen, Shiqian Ma, Anthony Man-Cho So, and Tong Zhang, "Proximal Gradient Method for Nonsmooth Optimization over the Stiefel Manifold". SIAM Journal on Optimization, 2020. Link Code

Conference papers

  1. Jinxin Wang, Jiang Hu, Shixiang Chen, Zengde Deng, Anthony Man-Cho So, "Decentralized Non-Smooth Optimization Over the Stiefel Manifold", IEEE SAM 2024.
  2. Yan Sun, Li Shen, Shixiang Chen, Liang Ding, Dacheng Tao, "Dynamic Regularized Sharpness Aware Minimization in Federated Learning: Approaching Global Consistency and Smooth Landscape", ICML 2023.
  3. Yibo Yang, Shixiang Chen, Liang Xie, Xiangtai Li, Zhouchen Lin, Dacheng Tao, "Inducing Neural Collapse in Imbalanced Learning: Do We Really Need a Learnable Classifier at the End of Deep Neural Network?" NeurIPS 2022. PDF
  4. Shixiang Chen, Alfredo Garcia, Mingyi Hong, Shahin Shahrampour, "Decentralized Riemannian Gradient Descent on the Stiefel Manifold", ICML 2021. PDF Code
  5. Shixiang Chen, Zengde Deng, Shiqian Ma and Anthony Man-Cho So, "Manifold proximal point algorithms for dual principal component pursuit and orthogonal dictionary learning", Asilomar Conference on Signals, Systems, and Computers, 2019.
  6. Shixiang Chen, Shiqian Ma and Wei Liu, "Geometric descent method for convex composite minimization", NeurIPS 2017. PDF

Note: * indicates equal contribution.