Geometric descent method for convex composite minimization. - Shixiang Chen; Shiqian Ma (CoRR, 2016)

Geometric Descent Method for Convex Composite Minimization. - Shixiang Chen; Shiqian Ma; Wei Liu 005 (NIPS, 2017)

An Alternating Manifold Proximal Gradient Method for Sparse PCA and Sparse CCA. - Shixiang Chen; Shiqian Ma; Lingzhou Xue; Hui Zou (CoRR, 2019)

Nonsmooth Optimization over Stiefel Manifold: Riemannian Subgradient Methods. - Xiao Li 009; Shixiang Chen; Zengde Deng; Qing Qu 001; Zhihui Zhu; Anthony Man-Cho So (CoRR, 2019)

Distributed Projected Subgradient Method for Weakly Convex Optimization. - Shixiang Chen; Alfredo García 001; Shahin Shahrampour (CoRR, 2020)

Proximal Gradient Method for Nonsmooth Optimization over the Stiefel Manifold. - Shixiang Chen; Shiqian Ma; Anthony Man-Cho So; Tong Zhang 001 (SIAM J. Optim., 2020)

An Alternating Manifold Proximal Gradient Method for Sparse Principal Component Analysis and Sparse Canonical Correlation Analysis. - Shixiang Chen; Shiqian Ma; Lingzhou Xue; Hui Zou (INFORMS J. Optim., 2020)

Decentralized Riemannian Gradient Descent on the Stiefel Manifold. - Shixiang Chen; Alfredo García 001; Mingyi Hong 001; Shahin Shahrampour (ICML, 2021)

Weakly Convex Optimization over Stiefel Manifold Using Riemannian Subgradient-Type Methods. - Xiao Li 009; Shixiang Chen; Zengde Deng; Qing Qu 001; Zhihui Zhu; Anthony Man-Cho So (SIAM J. Optim., 2021)

Manifold Proximal Point Algorithms for Dual Principal Component Pursuit and Orthogonal Dictionary Learning. - Shixiang Chen; Zengde Deng; Shiqian Ma; Anthony Man-Cho So (IEEE Trans. Signal Process., 2021)

Penalized Proximal Policy Optimization for Safe Reinforcement Learning. - Linrui Zhang; Li Shen 008; Long Yang 004; Shixiang Chen; Xueqian Wang 001; Bo Yuan 003; Dacheng Tao (IJCAI, 2022)

Inducing Neural Collapse in Imbalanced Learning: Do We Really Need a Learnable Classifier at the End of Deep Neural Network? - Yibo Yang; Shixiang Chen; Xiangtai Li; Liang Xie; Zhouchen Lin; Dacheng Tao (NeurIPS, 2022)

Do We Really Need a Learnable Classifier at the End of Deep Neural Network? - Yibo Yang; Liang Xie; Shixiang Chen; Xiangtai Li; Zhouchen Lin; Dacheng Tao (CoRR, 2022)

On Distributed Nonconvex Optimization: Projected Subgradient Method for Weakly Convex Problems in Networks. - Shixiang Chen; Alfredo García 001; Shahin Shahrampour (IEEE Trans. Autom. Control., 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 003 (INFORMS J. Optim., 2022)

Dynamic Regularized Sharpness Aware Minimization in Federated Learning: Approaching Global Consistency and Smooth Landscape. - Yan Sun; Li Shen 008; Shixiang Chen; Liang Ding 006; Dacheng Tao (ICML, 2023)

OmniForce: On Human-Centered, Large Model Empowered and Cloud-Edge Collaborative AutoML System. - Chao Xue; Wei Liu 005; Shuai Xie; Zhenfang Wang; Jiaxing Li; Xuyang Peng; Liang Ding 006; Shanshan Zhao 001; Qiong Cao; Yibo Yang; Fengxiang He; Bohua Cai; et al. (CoRR, 2023)

Decentralized Weakly Convex Optimization Over the Stiefel Manifold. - Jinxin Wang; Jiang Hu; Shixiang Chen; Zengde Deng; Anthony Man-Cho So (CoRR, 2023)

FedLALR: Client-Specific Adaptive Learning Rates Achieve Linear Speedup for Non-IID Data. - Hao Sun 019; Li Shen 008; Shixiang Chen; Jingwei Sun 001; Jing Li 047; Guangzhong Sun; Dacheng Tao (CoRR, 2023)

A fault diagnosis framework for autonomous vehicles with sensor self-diagnosis. - Haigen Min; Yukun Fang; Xia Wu 004; Xiaoping Lei; Shixiang Chen; Rui Teixeira; Bing Zhu; Xiangmo Zhao; Zhigang Xu 001 (Expert Syst. Appl., 2023)

Decentralized Non-Smooth Optimization Over the Stiefel Manifold. - Jinxin Wang; Jiang Hu; Shixiang Chen; Zengde Deng; Anthony Man-Cho So (SAM, 2024)

Uncertainty-aware Sensor Data Anomaly Detection for Autonomous Vehicles. - Shixiang Chen; Haigen Min; Yukun Fang; Xia Wu 004; Baolu Li; Xiangmo Zhao (IV, 2024)

Global Convergence of Decentralized Retraction-Free Optimization on the Stiefel Manifold. - Youbang Sun; Shixiang Chen; Alfredo García 001; Shahin Shahrampour (CoRR, 2024)

Local Linear Convergence of Infeasible Optimization With Orthogonal Constraints. - Youbang Sun; Shixiang Chen; Alfredo García 001; Shahin Shahrampour (IEEE Control. Syst. Lett., 2024)

Toward interpretable anomaly detection for autonomous vehicles with denoising variational transformer. - Haigen Min; Xiaoping Lei; Xia Wu 004; Yukun Fang; Shixiang Chen; Wuqi Wang; Xiangmo Zhao (Eng. Appl. Artif. Intell., 2024)

Nonsmooth Optimization over the Stiefel Manifold and Beyond: Proximal Gradient Method and Recent Variants. - Shixiang Chen; Shiqian Ma; Anthony Man-Cho So; Tong Zhang 001 (SIAM Rev., 2024)

Mechanisms Influencing the Digital Transformation Performance of Local Governments: Evidence from China. - Wei Zhou; Zhijie Lyu; Shixiang Chen (Syst., 2024)

AdaSAM: Boosting sharpness-aware minimization with adaptive learning rate and momentum for training deep neural networks. - Hao Sun 019; Li Shen 008; Qihuang Zhong; Liang Ding 006; Shixiang Chen; Jingwei Sun 001; Jing Li 047; Guangzhong Sun; Dacheng Tao (Neural Networks, 2024)

On the Local Linear Rate of Consensus on the Stiefel Manifold. - Shixiang Chen; Alfredo García 001; Mingyi Hong 001; Shahin Shahrampour (IEEE Trans. Autom. Control., 2024)

Constraint Boundary Wandering Framework: Enhancing Constrained Optimization With Deep Neural Networks. - Shuang Wu; Shixiang Chen; Li Shen 008; Lefei Zhang; Dacheng Tao (IEEE Trans. Pattern Anal. Mach. Intell., 2025)