Rongye Shi
Orcid: 0000-0003-4298-9358
According to our database1,
Rongye Shi
authored at least 27 papers
between 2016 and 2024.
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Bibliography
2024
ACM Trans. Inf. Syst., July, 2024
IEEE Trans Autom. Sci. Eng., April, 2024
Hierarchical Consensus-Based Multi-Agent Reinforcement Learning for Multi-Robot Cooperation Tasks.
CoRR, 2024
AdaptAUG: Adaptive Data Augmentation Framework for Multi-Agent Reinforcement Learning.
Proceedings of the IEEE International Conference on Robotics and Automation, 2024
Proceedings of the ECAI 2024 - 27th European Conference on Artificial Intelligence, 19-24 October 2024, Santiago de Compostela, Spain, 2024
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024
2023
Physics-Informed Deep Learning for Traffic State Estimation: A Survey and the Outlook.
Algorithms, June, 2023
Robust Data Sampling in Machine Learning: A Game-Theoretic Framework for Training and Validation Data Selection.
Games, February, 2023
Air-M: A Visual Reality Many-Agent Reinforcement Learning Platform for Large-Scale Aerial Unmanned System.
IROS, 2023
Proceedings of the ECAI 2023 - 26th European Conference on Artificial Intelligence, September 30 - October 4, 2023, Kraków, Poland, 2023
2022
Location Selection for Air Quality Monitoring With Consideration of Limited Budget and Estimation Error.
IEEE Trans. Mob. Comput., 2022
A Physics-Informed Deep Learning Paradigm for Traffic State and Fundamental Diagram Estimation.
IEEE Trans. Intell. Transp. Syst., 2022
TCACNet: Temporal and channel attention convolutional network for motor imagery classification of EEG-based BCI.
Inf. Process. Manag., 2022
ST-ICM: spatial-temporal inference calibration model for low cost fine-grained mobile sensing.
Proceedings of the ACM MobiCom '22: The 28th Annual International Conference on Mobile Computing and Networking, Sydney, NSW, Australia, October 17, 2022
2021
Improving the On-Vehicle Experience of Passengers Through SC-M*: A Scalable Multi-Passenger Multi-Criteria Mobility Planner.
IEEE Trans. Intell. Transp. Syst., 2021
A Physics-Informed Deep Learning Paradigm for Traffic State Estimation and Fundamental Diagram Discovery.
CoRR, 2021
OBELISC: Oscillator-Based Modelling and Control Using Efficient Neural Learning for Intelligent Road Traffic Signal Calculation.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track, 2021
TRAMESINO: Traffic Memory System for Intelligent Optimization of Road Traffic Control.
Proceedings of the Advanced Analytics and Learning on Temporal Data, 2021
Physics-Informed Deep Learning for Traffic State Estimation: A Hybrid Paradigm Informed By Second-Order Traffic Models.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021
2020
A Survey on Autonomous Vehicle Control in the Era of Mixed-Autonomy: From Physics-Based to AI-Guided Driving Policy Learning.
CoRR, 2020
2018
Generating Synthetic Passenger Data through Joint Traffic-Passenger Modeling and Simulation.
Proceedings of the 21st International Conference on Intelligent Transportation Systems, 2018
2017
LightNN: Filling the Gap between Conventional Deep Neural Networks and Binarized Networks.
Proceedings of the on Great Lakes Symposium on VLSI 2017, 2017
Second-Order Destination Inference using Semi-Supervised Self-Training for Entry-Only Passenger Data.
Proceedings of the Fourth IEEE/ACM International Conference on Big Data Computing, 2017
2016
On the design of phase locked loop oscillatory neural networks: Mitigation of transmission delay effects.
Proceedings of the 2016 International Joint Conference on Neural Networks, 2016