Detection of Uncertainty in Exceedance of Threshold (DUET): An Adversarial Patch Localizer. - Terence Jie Chua; Wenhan Yu; Chang Liu 093; Jun Zhao 007 (BDCAT, 2022)

Time Minimization in Hierarchical Federated Learning. - Chang Liu 093; Terence Jie Chua; Jun Zhao 007 (SEC, 2022)

Resource Allocation for Mobile Metaverse with the Internet of Vehicles over 6G Wireless Communications: A Deep Reinforcement Learning Approach. - Terence Jie Chua; Wenhan Yu; Jun Zhao 007 (WF-IoT, 2022)

Unified, User and Task (UUT) Centered Artificial Intelligence for Metaverse Edge Computing. - Terence Jie Chua; Wenhan Yu; Jun Zhao 007 (CoRR, 2022)

Mobile Edge Adversarial Detection for Digital Twinning to the Metaverse with Deep Reinforcement Learning. - Terence Jie Chua; Wenhan Yu; Jun Zhao 007 (ICC, 2023)

Virtual Reality in Metaverse Over Wireless Networks with User-Centered Deep Reinforcement Learning. - Wenhan Yu; Terence Jie Chua; Jun Zhao 007 (ICC, 2023)

Multi-Agent Deep Reinforcement Learning for Digital Twin over 6G Wireless Communication in the Metaverse. - Wenhan Yu; Terence Jie Chua; Jun Zhao 007 (INFOCOM Workshops, 2023)

Mobile Edge Computing and AI Enabled Web3 Metaverse over 6G Wireless Communications: A Deep Reinforcement Learning Approach. - Wenhan Yu; Terence Jie Chua; Jun Zhao 007 (VTC2023-Spring, 2023)

User-centric Heterogeneous-action Deep Reinforcement Learning for Virtual Reality in the Metaverse over Wireless Networks. - Wenhan Yu; Terence Jie Chua; Jun Zhao 007 (CoRR, 2023)

Play to Earn in the Metaverse with Mobile Edge Computing over Wireless Networks: A Deep Reinforcement Learning Approach. - Terence Jie Chua; Wenhan Yu; Jun Zhao 007 (CoRR, 2023)

FedPEAT: Convergence of Federated Learning, Parameter-Efficient Fine Tuning, and Emulator Assisted Tuning for Artificial Intelligence Foundation Models with Mobile Edge Computing. - Terence Jie Chua; Wenhan Yu; Jun Zhao 007; Kwok-Yan Lam (CoRR, 2023)

Orchestration of Emulator Assisted Mobile Edge Tuning for AI Foundation Models: A Multi-Agent Deep Reinforcement Learning Approach. - Wenhan Yu; Terence Jie Chua; Jun Zhao 007 (CoRR, 2023)

Asynchronous Hybrid Reinforcement Learning for Latency and Reliability Optimization in the Metaverse Over Wireless Communications. - Wenhan Yu; Terence Jie Chua; Jun Zhao 007 (IEEE J. Sel. Areas Commun., 2023)

Counterfactual Reward Estimation for Credit Assignment in Multi-agent Deep Reinforcement Learning over Wireless Video Transmission. - Wenhan Yu; Liangxin Qian; Terence Jie Chua; Jun Zhao 007 (ICDCS, 2024)

Optimization for the Metaverse over Mobile Edge Computing with Play to Earn. - Chang Liu 093; Terence Jie Chua; Jun Zhao 007 (INFOCOM, 2024)

Orchestration of Emulator Assisted 6G Mobile Edge Tuning for AI Foundation Models: A Multi-Agent Deep Reinforcement Learning Approach. - Wenhan Yu; Terence Jie Chua; Jun Zhao 007 (VTC Spring, 2024)

Play to Earn in Augmented Reality With Mobile Edge Computing Over Wireless Networks: A Deep Reinforcement Learning Approach. - Terence Jie Chua; Wenhan Yu; Jun Zhao 007 (IEEE Trans. Wirel. Commun., 2025)

Mobile Edge Adversarial Detection for Digital Twinning to the Metaverse: A Deep Reinforcement Learning Approach. - Terence Jie Chua; Wenhan Yu; Jun Zhao 007 (IEEE Trans. Wirel. Commun., 2025)