Shixiang Chen

According to our database, Shixiang Chen authored at least 24 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

On the Local Linear Rate of Consensus on the Stiefel Manifold.

Shixiang Chen, Alfredo Garcia, Mingyi Hong, Shahin Shahrampour

IEEE Trans. Autom. Control., April, 2024

AdaSAM: Boosting sharpness-aware minimization with adaptive learning rate and momentum for training deep neural networks.

Hao Sun, Li Shen, Qihuang Zhong, Liang Ding, Shixiang Chen, Jingwei Sun, Jing Li, Guangzhong Sun, Dacheng Tao

Neural Networks, January, 2024

Mechanisms Influencing the Digital Transformation Performance of Local Governments: Evidence from China.

Wei Zhou, Zhijie Lyu, Shixiang Chen

Syst., 2024

2023

A fault diagnosis framework for autonomous vehicles with sensor self-diagnosis.

Haigen Min, Yukun Fang, Xia Wu, Xiaoping Lei, Shixiang Chen, Rui Teixeira, Bing Zhu, Xiangmo Zhao, Zhigang Xu

Expert Syst. Appl., August, 2023

FedLALR: Client-Specific Adaptive Learning Rates Achieve Linear Speedup for Non-IID Data.

Hao Sun, Li Shen, Shixiang Chen, Jingwei Sun, Jing Li, Guangzhong Sun, Dacheng Tao

CoRR, 2023

Decentralized Weakly Convex Optimization Over the Stiefel Manifold.

Jinxin Wang, Jiang Hu, Shixiang Chen, Zengde Deng, Anthony Man-Cho So

CoRR, 2023

AdaSAM: Boosting Sharpness-Aware Minimization with Adaptive Learning Rate and Momentum for Training Deep Neural Networks.

Hao Sun, Li Shen, Qihuang Zhong, Liang Ding, Shixiang Chen, Jingwei Sun, Jing Li, Guangzhong Sun, Dacheng Tao

CoRR, 2023

OmniForce: On Human-Centered, Large Model Empowered and Cloud-Edge Collaborative AutoML System.

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

CoRR, 2023

Dynamic Regularized Sharpness Aware Minimization in Federated Learning: Approaching Global Consistency and Smooth Landscape.

Yan Sun, Li Shen, Shixiang Chen, Liang Ding, Dacheng Tao

Proceedings of the International Conference on Machine Learning, 2023

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 J. Optim., April, 2022

On Distributed Nonconvex Optimization: Projected Subgradient Method for Weakly Convex Problems in Networks.

Shixiang Chen, Alfredo Garcia, Shahin Shahrampour

IEEE Trans. Autom. Control., 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

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

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Penalized Proximal Policy Optimization for Safe Reinforcement Learning.

Linrui Zhang, Li Shen, Long Yang, Shixiang Chen, Xueqian Wang, Bo Yuan, Dacheng Tao

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

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

Weakly Convex Optimization over Stiefel Manifold Using Riemannian Subgradient-Type Methods.

Xiao Li, Shixiang Chen, Zengde Deng, Qing Qu, Zhihui Zhu, Anthony Man-Cho So

SIAM J. Optim., 2021

Decentralized Riemannian Gradient Descent on the Stiefel Manifold.

Shixiang Chen, Alfredo Garcia, Mingyi Hong, Shahin Shahrampour

Proceedings of the 38th International Conference on Machine Learning, 2021

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., July, 2020

Proximal Gradient Method for Nonsmooth Optimization over the Stiefel Manifold.

Shixiang Chen, Shiqian Ma, Anthony Man-Cho So, Tong Zhang

SIAM J. Optim., 2020

Distributed Projected Subgradient Method for Weakly Convex Optimization.

Shixiang Chen, Alfredo Garcia, Shahin Shahrampour

CoRR, 2020

2019

Nonsmooth Optimization over Stiefel Manifold: Riemannian Subgradient Methods.

Xiao Li, Shixiang Chen, Zengde Deng, Qing Qu, Zhihui Zhu, Anthony Man-Cho So

CoRR, 2019

An Alternating Manifold Proximal Gradient Method for Sparse PCA and Sparse CCA.

Shixiang Chen, Shiqian Ma, Lingzhou Xue, Hui Zou

CoRR, 2019

2017

Geometric Descent Method for Convex Composite Minimization.

Shixiang Chen, Shiqian Ma, Wei Liu

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2016

Geometric descent method for convex composite minimization.

Shixiang Chen, Shiqian Ma

CoRR, 2016