Shixiang Chen

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 35

Top Topics

Gradient Method

Global Consistency

Principal Component Analysis

Top Venues

INFORMS J. Optim.

Publications

Youbang Sun, Shixiang Chen, Alfredo García, Shahin Shahrampour
Global Convergence of Decentralized Retraction-Free Optimization on the Stiefel Manifold. CoRR (2024)
Shixiang Chen, Haigen Min, Yukun Fang, Xia Wu, Baolu Li, Xiangmo Zhao
Uncertainty-aware Sensor Data Anomaly Detection for Autonomous Vehicles. IV (2024)
Haigen Min, Xiaoping Lei, Xia Wu, Yukun Fang, Shixiang Chen, Wuqi Wang, Xiangmo Zhao
Toward interpretable anomaly detection for autonomous vehicles with denoising variational transformer. Eng. Appl. Artif. Intell. 129 (2024)
Shixiang Chen, Shiqian Ma, Anthony Man-Cho So, Tong Zhang
Nonsmooth Optimization over the Stiefel Manifold and Beyond: Proximal Gradient Method and Recent Variants. SIAM Rev. 66 (2) (2024)
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 169 (2024)
Shixiang Chen, Alfredo García, Mingyi Hong, Shahin Shahrampour
On the Local Linear Rate of Consensus on the Stiefel Manifold. IEEE Trans. Autom. Control. 69 (4) (2024)
Wei Zhou, Zhijie Lyu, Shixiang Chen
Mechanisms Influencing the Digital Transformation Performance of Local Governments: Evidence from China. Syst. 12 (1) (2024)
Hao Sun, Li Shen, Shixiang Chen, Jingwei Sun, Jing Li, Guangzhong Sun, Dacheng Tao
FedLALR: Client-Specific Adaptive Learning Rates Achieve Linear Speedup for Non-IID Data. CoRR (2023)
Haigen Min, Yukun Fang, Xia Wu, Xiaoping Lei, Shixiang Chen, Rui Teixeira, Bing Zhu, Xiangmo Zhao, Zhigang Xu
A fault diagnosis framework for autonomous vehicles with sensor self-diagnosis. Expert Syst. Appl. 224 (2023)
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)
Chao Xue, Wei Liu, Shuai Xie, Zhenfang Wang, Jiaxing Li, Xuyang Peng, Liang Ding, Shanshan Zhao, Qiong Cao, Yibo Yang, Fengxiang He, Bohua Cai, Rongcheng Bian, Yiyan Zhao, Heliang Zheng, Xiangyang Liu, Dongkai Liu, Daqing Liu, Li Shen, Chang Li, Shijin Zhang, Yukang Zhang, Guanpu Chen, Shixiang Chen, Yibing Zhan, Jing Zhang, Chaoyue Wang, Dacheng Tao
OmniForce: On Human-Centered, Large Model Empowered and Cloud-Edge Collaborative AutoML System. CoRR (2023)
Yan Sun, Li Shen, Shixiang Chen, Liang Ding, Dacheng Tao
Dynamic Regularized Sharpness Aware Minimization in Federated Learning: Approaching Global Consistency and Smooth Landscape. CoRR (2023)
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. CoRR (2023)
Jinxin Wang, Jiang Hu, Shixiang Chen, Zengde Deng, Anthony Man-Cho So
Decentralized Weakly Convex Optimization Over the Stiefel Manifold. CoRR (2023)
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 J. Optim. 4 (2) (2022)
Yibo Yang, Liang Xie, Shixiang Chen, Xiangtai Li, Zhouchen Lin, Dacheng Tao
Do We Really Need a Learnable Classifier at the End of Deep Neural Network? CoRR (2022)
Yibo Yang, Shixiang Chen, Xiangtai Li, Liang Xie, 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)
Linrui Zhang, Li Shen, Long Yang, Shixiang Chen, Xueqian Wang, Bo Yuan, Dacheng Tao
Penalized Proximal Policy Optimization for Safe Reinforcement Learning. IJCAI (2022)
Shixiang Chen, Alfredo Garcia, Shahin Shahrampour
On Distributed Nonconvex Optimization: Projected Subgradient Method for Weakly Convex Problems in Networks. IEEE Trans. Autom. Control. 67 (2) (2022)
Linrui Zhang, Li Shen, Long Yang, Shixiang Chen, Bo Yuan, Xueqian Wang, Dacheng Tao
Penalized Proximal Policy Optimization for Safe Reinforcement Learning. CoRR (2022)
Shixiang Chen, Alfredo Garcia, Mingyi Hong, Shahin Shahrampour
Decentralized Riemannian Gradient Descent on the Stiefel Manifold. CoRR (2021)
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 J. Optim. 31 (3) (2021)
Shixiang Chen, Alfredo Garcia, Mingyi Hong, Shahin Shahrampour
Decentralized Riemannian Gradient Descent on the Stiefel Manifold. ICML (2021)
Shixiang Chen, Zengde Deng, Shiqian Ma, Anthony Man-Cho So
Manifold Proximal Point Algorithms for Dual Principal Component Pursuit and Orthogonal Dictionary Learning. IEEE Trans. Signal Process. 69 (2021)
Shixiang Chen, Alfredo Garcia, Mingyi Hong, Shahin Shahrampour
On the Local Linear Rate of Consensus on the Stiefel Manifold. CoRR (2021)
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. CoRR (2020)
Shixiang Chen, Shiqian Ma, Anthony Man-Cho So, Tong Zhang
Proximal Gradient Method for Nonsmooth Optimization over the Stiefel Manifold. SIAM J. Optim. 30 (1) (2020)
Shixiang Chen, Zengde Deng, Shiqian Ma, Anthony Man-Cho So
Manifold Proximal Point Algorithms for Dual Principal Component Pursuit and Orthogonal Dictionary Learning. CoRR (2020)
Shixiang Chen, Alfredo Garcia, Shahin Shahrampour
Distributed Projected Subgradient Method for Weakly Convex Optimization. CoRR (2020)
Shixiang Chen, Shiqian Ma, Lingzhou Xue, Hui Zou
An Alternating Manifold Proximal Gradient Method for Sparse Principal Component Analysis and Sparse Canonical Correlation Analysis. INFORMS J. Optim. 2 (3) (2020)
Xiao Li, Shixiang Chen, Zengde Deng, Qing Qu, Zhihui Zhu, Anthony Man-Cho So
Nonsmooth Optimization over Stiefel Manifold: Riemannian Subgradient Methods. CoRR (2019)
Shixiang Chen, Shiqian Ma, Lingzhou Xue, Hui Zou
An Alternating Manifold Proximal Gradient Method for Sparse PCA and Sparse CCA. CoRR (2019)
Shixiang Chen, Zengde Deng, Shiqian Ma, Anthony Man-Cho So
Manifold Proximal Point Algorithms for Dual Principal Component Pursuit and Orthogonal Dictionary Learning. ACSSC (2019)
Shixiang Chen, Shiqian Ma, Wei Liu
Geometric Descent Method for Convex Composite Minimization. NIPS (2017)
Shixiang Chen, Shiqian Ma
Geometric descent method for convex composite minimization. CoRR (2016)