Shixiang Chen - RankMe

42 papers A* 4C 1Misc 1Journal 34Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Enhanced anomaly interpretation in intelligent vehicles: A causal constraint graph attention network for root cause diagnosis. Eng. Appl. Artif. Intell. Shixiang Chen, Haigen Min, Xia Wu, Xiangmo Zhao
2025	J	`jnl`	ADARL: Adaptive Low-Rank Structures for Robust Policy Learning under Uncertainty. CoRR Chenliang Li, Junyu Leng, Jiaxiang Li, Youbang Sun, Shixiang Chen, Shahin Shahrampour, Alfredo García
2025	J	`jnl`	Constraint Boundary Wandering Framework: Enhancing Constrained Optimization With Deep Neural Networks. IEEE Trans. Pattern Anal. Mach. Intell. Shuang Wu, Shixiang Chen, Li Shen, Lefei Zhang, Dacheng Tao
2025	J	`jnl`	Distributed Stochastic Proximal Algorithm on Riemannian Submanifolds for Weakly-convex Functions. CoRR Jishu Zhao, Xi Wang, Jinlong Lei, Shixiang Chen
2024	J	`jnl`	AdaSAM: Boosting sharpness-aware minimization with adaptive learning rate and momentum for training deep neural networks. Neural Networks Hao Sun, Li Shen, Qihuang Zhong, Liang Ding, Shixiang Chen, Jingwei Sun, Jing Li, Guangzhong Sun, Dacheng Tao
2024	—	`conf`	Decentralized Non-Smooth Optimization Over the Stiefel Manifold. SAM Jinxin Wang, Jiang Hu, Shixiang Chen, Zengde Deng, Anthony Man-Cho So
2024	J	`jnl`	Global Convergence of Decentralized Retraction-Free Optimization on the Stiefel Manifold. CoRR Youbang Sun, Shixiang Chen, Alfredo García, Shahin Shahrampour
2024	J	`jnl`	Local Linear Convergence of Infeasible Optimization With Orthogonal Constraints. IEEE Control. Syst. Lett. Youbang Sun, Shixiang Chen, Alfredo García, Shahin Shahrampour
2024	J	`jnl`	Local Linear Convergence of Infeasible Optimization with Orthogonal Constraints. CoRR Youbang Sun, Shixiang Chen, Alfredo García, Shahin Shahrampour
2024	J	`jnl`	Mechanisms Influencing the Digital Transformation Performance of Local Governments: Evidence from China. Syst. Wei Zhou, Zhijie Lyu, Shixiang Chen
2024	J	`jnl`	Nonsmooth Optimization over the Stiefel Manifold and Beyond: Proximal Gradient Method and Recent Variants. SIAM Rev. Shixiang Chen, Shiqian Ma, Anthony Man-Cho So, Tong Zhang
2024	J	`jnl`	On the Local Linear Rate of Consensus on the Stiefel Manifold. IEEE Trans. Autom. Control. Shixiang Chen, Alfredo García, Mingyi Hong, Shahin Shahrampour
2024	J	`jnl`	Toward interpretable anomaly detection for autonomous vehicles with denoising variational transformer. Eng. Appl. Artif. Intell. Haigen Min, Xiaoping Lei, Xia Wu, Yukun Fang, Shixiang Chen, Wuqi Wang, Xiangmo Zhao
2024	C	`conf`	Uncertainty-aware Sensor Data Anomaly Detection for Autonomous Vehicles. IV Shixiang Chen, Haigen Min, Yukun Fang, Xia Wu, Baolu Li, Xiangmo Zhao
2023	J	`jnl`	A fault diagnosis framework for autonomous vehicles with sensor self-diagnosis. Expert Syst. Appl. Haigen Min, Yukun Fang, Xia Wu, Xiaoping Lei, Shixiang Chen, Rui Teixeira, Bing Zhu, Xiangmo Zhao, Zhigang Xu
2023	J	`jnl`	AdaSAM: Boosting Sharpness-Aware Minimization with Adaptive Learning Rate and Momentum for Training Deep Neural Networks. CoRR Hao Sun, Li Shen, Qihuang Zhong, Liang Ding, Shixiang Chen, Jingwei Sun, Jing Li, Guangzhong Sun, Dacheng Tao
2023	J	`jnl`	Decentralized Weakly Convex Optimization Over the Stiefel Manifold. CoRR Jinxin Wang, Jiang Hu, Shixiang Chen, Zengde Deng, Anthony Man-Cho So
2023	A*	`conf`	Dynamic Regularized Sharpness Aware Minimization in Federated Learning: Approaching Global Consistency and Smooth Landscape. ICML Yan Sun, Li Shen, Shixiang Chen, Liang Ding, Dacheng Tao
2023	J	`jnl`	Dynamic Regularized Sharpness Aware Minimization in Federated Learning: Approaching Global Consistency and Smooth Landscape. CoRR Yan Sun, Li Shen, Shixiang Chen, Liang Ding, Dacheng Tao
2023	J	`jnl`	FedLALR: Client-Specific Adaptive Learning Rates Achieve Linear Speedup for Non-IID Data. CoRR Hao Sun, Li Shen, Shixiang Chen, Jingwei Sun, Jing Li, Guangzhong Sun, Dacheng Tao
2023	J	`jnl`	OmniForce: On Human-Centered, Large Model Empowered and Cloud-Edge Collaborative AutoML System. CoRR 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
2022	J	`jnl`	A Manifold Proximal Linear Method for Sparse Spectral Clustering with Application to Single-Cell RNA Sequencing Data Analysis. INFORMS J. Optim. Zhongruo Wang, Bingyuan Liu, Shixiang Chen, Shiqian Ma, Lingzhou Xue, Hongyu Zhao
2022	J	`jnl`	Do We Really Need a Learnable Classifier at the End of Deep Neural Network? CoRR Yibo Yang, Liang Xie, Shixiang Chen, Xiangtai Li, Zhouchen Lin, Dacheng Tao
2022	A*	`conf`	Inducing Neural Collapse in Imbalanced Learning: Do We Really Need a Learnable Classifier at the End of Deep Neural Network? NeurIPS Yibo Yang, Shixiang Chen, Xiangtai Li, Liang Xie, Zhouchen Lin, Dacheng Tao
2022	J	`jnl`	On Distributed Nonconvex Optimization: Projected Subgradient Method for Weakly Convex Problems in Networks. IEEE Trans. Autom. Control. Shixiang Chen, Alfredo García, Shahin Shahrampour
2022	A*	`conf`	Penalized Proximal Policy Optimization for Safe Reinforcement Learning. IJCAI Linrui Zhang, Li Shen, Long Yang, Shixiang Chen, Xueqian Wang, Bo Yuan, Dacheng Tao
2022	J	`jnl`	Penalized Proximal Policy Optimization for Safe Reinforcement Learning. CoRR Linrui Zhang, Li Shen, Long Yang, Shixiang Chen, Bo Yuan, Xueqian Wang, Dacheng Tao
2021	A*	`conf`	Decentralized Riemannian Gradient Descent on the Stiefel Manifold. ICML Shixiang Chen, Alfredo García, Mingyi Hong, Shahin Shahrampour
2021	J	`jnl`	Decentralized Riemannian Gradient Descent on the Stiefel Manifold. CoRR Shixiang Chen, Alfredo García, Mingyi Hong, Shahin Shahrampour
2021	J	`jnl`	Manifold Proximal Point Algorithms for Dual Principal Component Pursuit and Orthogonal Dictionary Learning. IEEE Trans. Signal Process. Shixiang Chen, Zengde Deng, Shiqian Ma, Anthony Man-Cho So
2021	J	`jnl`	On the Local Linear Rate of Consensus on the Stiefel Manifold. CoRR Shixiang Chen, Alfredo García, Mingyi Hong, Shahin Shahrampour
2021	J	`jnl`	Weakly Convex Optimization over Stiefel Manifold Using Riemannian Subgradient-Type Methods. SIAM J. Optim. Xiao Li, Shixiang Chen, Zengde Deng, Qing Qu, Zhihui Zhu, Anthony Man-Cho So
2020	J	`jnl`	A Manifold Proximal Linear Method for Sparse Spectral Clustering with Application to Single-Cell RNA Sequencing Data Analysis. CoRR Zhongruo Wang, Bingyuan Liu, Shixiang Chen, Shiqian Ma, Lingzhou Xue, Hongyu Zhao
2020	J	`jnl`	An Alternating Manifold Proximal Gradient Method for Sparse Principal Component Analysis and Sparse Canonical Correlation Analysis. INFORMS J. Optim. Shixiang Chen, Shiqian Ma, Lingzhou Xue, Hui Zou
2020	J	`jnl`	Distributed Projected Subgradient Method for Weakly Convex Optimization. CoRR Shixiang Chen, Alfredo García, Shahin Shahrampour
2020	J	`jnl`	Manifold Proximal Point Algorithms for Dual Principal Component Pursuit and Orthogonal Dictionary Learning. CoRR Shixiang Chen, Zengde Deng, Shiqian Ma, Anthony Man-Cho So
2020	J	`jnl`	Proximal Gradient Method for Nonsmooth Optimization over the Stiefel Manifold. SIAM J. Optim. Shixiang Chen, Shiqian Ma, Anthony Man-Cho So, Tong Zhang
2019	J	`jnl`	An Alternating Manifold Proximal Gradient Method for Sparse PCA and Sparse CCA. CoRR Shixiang Chen, Shiqian Ma, Lingzhou Xue, Hui Zou
2019	Misc	`conf`	Manifold Proximal Point Algorithms for Dual Principal Component Pursuit and Orthogonal Dictionary Learning. ACSSC Shixiang Chen, Zengde Deng, Shiqian Ma, Anthony Man-Cho So
2019	J	`jnl`	Nonsmooth Optimization over Stiefel Manifold: Riemannian Subgradient Methods. CoRR Xiao Li, Shixiang Chen, Zengde Deng, Qing Qu, Zhihui Zhu, Anthony Man-Cho So
2017	—	`conf`	Geometric Descent Method for Convex Composite Minimization. NIPS Shixiang Chen, Shiqian Ma, Wei Liu
2016	J	`jnl`	Geometric descent method for convex composite minimization. CoRR Shixiang Chen, Shiqian Ma