Shuhang Chen

According to our database, Shuhang Chen authored at least 35 papers between 2014 and 2024.

Collaborative distances:

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

2024

The ODE Method for Stochastic Approximation and Reinforcement Learning with Markovian Noise.

Shuze Liu, Shuhang Chen, Shangtong Zhang

CoRR, 2024

2023

GRID: A Platform for General Robot Intelligence Development.

Sai Vemprala, Shuhang Chen, Abhinav Shukla, Dinesh Narayanan, Ashish Kapoor

CoRR, 2023

A new Energy-Saving Sector Clustering Data Aggregation Method in Wireless Sensor Networks: Energy saving sector clustering data aggregation method.

Shuhang Chen, Feng Xu, Kaiming Su

Proceedings of the 2nd International Conference on Signal Processing, 2023

IDDR-NGP: Incorporating Detectors for Distractors Removal with Instant Neural Radiance Field.

Xianliang Huang, Jiajie Gou, Shuhang Chen, Zhizhou Zhong, Jihong Guan, Shuigeng Zhou

Proceedings of the 31st ACM International Conference on Multimedia, 2023

PACT: Perception-Action Causal Transformer for Autoregressive Robotics Pre-Training.

Rogerio Bonatti, Sai Vemprala, Shuang Ma, Felipe Frujeri, Shuhang Chen, Ashish Kapoor

IROS, 2023

Is Imitation All You Need? Generalized Decision-Making with Dual-Phase Training.

Yao Wei, Yanchao Sun, Ruijie Zheng, Sai Vemprala, Rogerio Bonatti, Shuhang Chen, Ratnesh Madaan, Zhongjie Ba, Ashish Kapoor, Shuang Ma

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Tracking the Dynamic Neural Connectivity via Conjugate Gradient Optimization.

Mingdong Li, Shuhang Chen, Zhijia Zhao, Yiwen Wang

Proceedings of the 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2023

A Bayesian Decoder Representing Single-Directional Connectivity between Neurons in Brain-Machine Interface.

Shuhang Chen, Yiwen Wang

Proceedings of the 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2023

2022

Waste Collection and Transportation Supervision Based on Improved YOLOv3 Model.

Yanhong He, Junfeng Li, Shuhang Chen, Yining Xu, Jia Liang

IEEE Access, 2022

Modeling Neural Connectivity in a Point-Process Analogue of Kalman Filter.

Mingdong Li, Shuhang Chen, Xi Liu, Zhiwei Song, Yiwen Wang

Proceedings of the 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2022

2021

Hierarchical Dynamical Model for Multiple Cortical Neural Decoding.

Xi Liu, Xiang Shen, Shuhang Chen, Xiang Zhang, Yifan Huang, Yueming Wang, Yiwen Wang

Neural Comput., 2021

Revisiting the ODE Method for Recursive Algorithms: Fast Convergence Using Quasi Stochastic Approximation.

Shuhang Chen, Adithya M. Devraj, Andrey Berstein, Sean P. Meyn

J. Syst. Sci. Complex., 2021

A Nonlinear Maximum Correntropy Information Filter for High-Dimensional Neural Decoding.

Xi Liu, Shuhang Chen, Xiang Shen, Xiang Zhang, Yiwen Wang

Entropy, 2021

The ODE Method for Asymptotic Statistics in Stochastic Approximation and Reinforcement Learning.

Vivek S. Borkar, Shuhang Chen, Adithya M. Devraj, Ioannis Kontoyiannis, Sean P. Meyn

CoRR, 2021

Developing a Framework for Spatial Effects of Smart Cities Based on Spatial Econometrics.

Kongling Liu, Mengjun Wang, Jianchang Li, Jingjing Huang, Xuhui Huang, Shuhang Chen, Baoquan Cheng

Complex., 2021

Considering Neural Connectivity in Point Process Decoder for Brain-Machine Interface^*.

Shuhang Chen, Xi Liu, Yiwen Wang

Proceedings of the 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2021

Accelerating Optimization and Reinforcement Learning with Quasi Stochastic Approximation.

Shuhang Chen, Adithya M. Devraj, Andrey Bernstein, Sean P. Meyn

Proceedings of the 2021 American Control Conference, 2021

2020

A Decision-Making Model Using Machine Learning for Improving Dispatching Efficiency in Chengdu Shuangliu Airport.

Yingmiao Qian, Shuhang Chen, Jianchang Li, Qinxin Ren, Jinfu Zhu, Ruijia Yuan, Hao Su

Complex., 2020

Investigating Co-Activation between Medial Prefrontal and Primary Motor Cortical Spike Trains during Task Learning.

Shenghui Wu, Cunle Qian, Xiang Shen, Xiang Zhang, Yifan Huang, Shuhang Chen, Yiwen Wang

Proceedings of the 2020 IEEE International Conference on Systems, Man, and Cybernetics, 2020

Decoding Reward Information from Local Field Potential and Spikes in Medial Prefrontal Cortex of Rats.

Yifan Huang, Xiang Shen, Xiang Zhang, Shuhang Chen, Yiwen Wang

Proceedings of the 2020 IEEE International Conference on Systems, Man, and Cybernetics, 2020

Zap Q-Learning With Nonlinear Function Approximation.

Shuhang Chen, Adithya M. Devraj, Fan Lu, Ana Busic, Sean P. Meyn

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Reinforcement Learning based Decoding Using Internal Reward for Time Delayed Task in Brain Machine Interfaces.

Xiang Shen, Xiang Zhang, Yifan Huang, Shuhang Chen, Yiwen Wang

Proceedings of the 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2020

Estimating Neural Modulation via Adaptive Point Process Method in Brain-machine Interface.

Shuhang Chen, Xiang Zhang, Xiang Shen, Yifan Huang, Yiwen Wang

Proceedings of the 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2020

Zap Q-Learning for Optimal Stopping.

Shuhang Chen, Adithya M. Devraj, Ana Busic, Sean P. Meyn

Proceedings of the 2020 American Control Conference, 2020

Explicit Mean-Square Error Bounds for Monte-Carlo and Linear Stochastic Approximation.

Shuhang Chen, Adithya M. Devraj, Ana Busic, Sean P. Meyn

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Zap Q-Learning With Nonlinear Function Approximation.

Shuhang Chen, Adithya M. Devraj, Ana Busic, Sean P. Meyn

CoRR, 2019

Zap~Q-Learning for Optimal Stopping Time Problems.

Shuhang Chen, Adithya M. Devraj, Ana Busic, Sean P. Meyn

CoRR, 2019

Decoding Transition between Kinematics Stages for Brain-Machine Interface.

Shuhang Chen, Xiang Zhang, Xiang Shen, Yifan Huang, Yiwen Wang

Proceedings of the 2019 IEEE International Conference on Systems, Man and Cybernetics, 2019

Modelling mPFC Activities in Reinforcement Learning Framework for Brain-Machine Interfaces.

Xiang Shen, Xiang Zhang, Yifan Huang, Shuhang Chen, Yiwen Wang

Proceedings of the 2019 9th International IEEE/EMBS Conference on Neural Engineering (NER), 2019

Time-frequency Relevancy Analysis between Local Field Potentials and Lever Pressing Motion of Rats.

Yifan Huang, Xiang Shen, Yiwen Wang, Shuhang Chen, Xiang Zhang

Proceedings of the 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2019

2018

Tracking the Time Varying Neural Tuning via Adam on Point Process Observations.

Zitong Zhang, Shuhang Chen, Zaiyue Yang, Yiwen Wang

Proceedings of the 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2018

2017

Disentangling inter-subject variations: Automatic localization of ventricular tachycardia origin from 12-lead electrocardiograms.

Shuhang Chen, Prashnna K. Gyawali, Huafeng Liu, B. Milan Horácek, John L. Sapp, Linwei Wang

Proceedings of the 14th IEEE International Symposium on Biomedical Imaging, 2017

Automatic Coordinate Prediction of the Exit of Ventricular Tachycardia from 12-Lead Electrocardiogram.

Prashnna K. Gyawali, Shuhang Chen, Huafeng Liu, B. Milan Horácek, John L. Sapp, Linwei Wang

Proceedings of the Computing in Cardiology, 2017

2015

Simultaneous Reconstruction and Segmentation of Dynamic PET via Low-Rank and Sparse Matrix Decomposition.

Shuhang Chen, Huafeng Liu, Zhenghui Hu, Heye Zhang, Pengcheng Shi, Yunmei Chen

IEEE Trans. Biomed. Eng., 2015

2014

Simultaneous reconstruction and segmentation for dynamic PET: A low rank framework.

Shuhang Chen, Zhi Chen, Zhenghui Hu, Yunmei Chen, Huafeng Liu

Proceedings of the IEEE 11th International Symposium on Biomedical Imaging, 2014