Jiayu Chen

Orcid: 0000-0002-7708-5247

Affiliations:
  • University of Hong Kong, Department of Data and Systems Engineering, Hong Kong
  • Purdue University, School of Industrial Engineering, West Lafayette, IN, USA (PhD 2024)
  • Peking University, College of Engineering, Beijing, China (2016 - 2020)


According to our database1, Jiayu Chen authored at least 30 papers between 2019 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Bibliography

2025
Learning Explainable Stock Predictions with Tweets Using Mixture of Experts.
CoRR, July, 2025

Behavior Foundation Model: Towards Next-Generation Whole-Body Control System of Humanoid Robots.
CoRR, June, 2025

Policy-Driven World Model Adaptation for Robust Offline Model-based Reinforcement Learning.
CoRR, May, 2025

Rack Position Optimization in Large-Scale Heterogeneous Data Centers.
CoRR, April, 2025

Learning-Based Two-Tiered Online Optimization of Region-Wide Datacenter Resource Allocation.
IEEE Trans. Netw. Serv. Manag., February, 2025

Mining Intraday Risk Factor Collections via Hierarchical Reinforcement Learning based on Transferred Options.
CoRR, January, 2025

Order-Optimal Global Convergence for Actor-Critic with General Policy and Neural Critic Parametrization.
Proceedings of the Conference on Uncertainty in Artificial Intelligence, 2025

Variational Offline Multi-agent Skill Discovery.
Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence, 2025

2024
Hierarchical Adversarial Inverse Reinforcement Learning.
IEEE Trans. Neural Networks Learn. Syst., December, 2024

Reinforced Sequential Decision-Making for Sepsis Treatment: The PosNegDM Framework With Mortality Classifier and Transformer.
IEEE J. Biomed. Health Informatics, May, 2024

Global Convergence Guarantees for Federated Policy Gradient Methods with Adversaries.
Trans. Mach. Learn. Res., 2024

Deep Generative Models for Offline Policy Learning: Tutorial, Survey, and Perspectives on Future Directions.
Trans. Mach. Learn. Res., 2024

Bayes Adaptive Monte Carlo Tree Search for Offline Model-based Reinforcement Learning.
CoRR, 2024

Variational Offline Multi-agent Skill Discovery.
CoRR, 2024

2023
Learning Multiagent Options for Tabular Reinforcement Learning using Factor Graphs.
IEEE Trans. Artif. Intell., October, 2023

Scalable Multi-agent Skill Discovery based on Kronecker Graphs.
CoRR, 2023

Two-tiered Online Optimization of Region-wide Datacenter Resource Allocation via Deep Reinforcement Learning.
CoRR, 2023

Hierarchical Deep Counterfactual Regret Minimization.
CoRR, 2023

A Unified Algorithm Framework for Unsupervised Discovery of Skills based on Determinantal Point Process.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Option-Aware Adversarial Inverse Reinforcement Learning for Robotic Control.
Proceedings of the IEEE International Conference on Robotics and Automation, 2023

Multi-task Hierarchical Adversarial Inverse Reinforcement Learning.
Proceedings of the International Conference on Machine Learning, 2023

Impact of AI on Mobile Computing: A Systematic Review from a Human Factors Perspective.
Proceedings of the HCI International 2023 - Late Breaking Papers, 2023

2022
ODPP: A Unified Algorithm Framework for Unsupervised Option Discovery based on Determinantal Point Process.
CoRR, 2022

Multi-agent Deep Covering Option Discovery.
CoRR, 2022

Multi-agent Covering Option Discovery based on Kronecker Product of Factor Graphs.
CoRR, 2022

Scalable Multi-agent Covering Option Discovery based on Kronecker Graphs.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Multi-agent Covering Option Discovery through Kronecker Product of Factor Graphs.
Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems, 2022

2021
Decision Making for Autonomous Driving via Augmented Adversarial Inverse Reinforcement Learning.
Proceedings of the IEEE International Conference on Robotics and Automation, 2021

DeepFreight: A Model-free Deep-reinforcement-learning-based Algorithm for Multi-transfer Freight Delivery.
Proceedings of the Thirty-First International Conference on Automated Planning and Scheduling, 2021

2019
Supervised Learning for Semantic Segmentation of 3D LiDAR Data.
Proceedings of the 2019 IEEE Intelligent Vehicles Symposium, 2019


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