Performance bound analysis for crowdsourced mobile video streaming. - Lin Gao 001; Ming Tang 006; Haitian Pang; Jianwei Huang 001; Lifeng Sun (CISS, 2016)

Crowdsourced mobility prediction based on spatio-temporal contexts. - Haitian Pang; Peng Wang 012; Lin Gao 001; Ming Tang 006; Jianwei Huang 001; Lifeng Sun (ICC, 2016)

A multi-dimensional auction mechanism for mobile crowdsourced video streaming. - Ming Tang 006; Lin Gao 001; Haitian Pang; Jianwei Huang 001; Lifeng Sun (WiOpt, 2016)

A General Framework for Crowdsourcing Mobile Communication, Computation, and Caching. - Ming Tang 006; Lin Gao 001; Jianwei Huang 001 (GLOBECOM, 2017)

MOMD: A multi-object multi-dimensional auction for crowdsourced mobile video streaming. - Ming Tang 006; Shou Wang; Lin Gao 001; Jianwei Huang 001; Lifeng Sun (INFOCOM, 2017)

Optimizations and Economics of Crowdsourced Mobile Streaming. - Ming Tang 006; Lin Gao 001; Haitian Pang; Jianwei Huang 001; Lifeng Sun (IEEE Commun. Mag., 2017)

Enabling Edge Cooperation in Tactile Internet via 3C Resource Sharing. - Ming Tang 006; Lin Gao 001; Jianwei Huang 001 (IEEE J. Sel. Areas Commun., 2018)

Multi-Dimensional Auction Mechanisms for Crowdsourced Mobile Video Streaming. - Ming Tang 006; Haitian Pang; Shou Wang; Lin Gao 001; Jianwei Huang 001; Lifeng Sun (IEEE/ACM Trans. Netw., 2018)

How to Earn Money in Live Streaming Platforms? - A Study of Donation-Based Markets. - Ming Tang 006; Jianwei Huang 001 (INFOCOM, 2019)

Multi-User Cooperative Mobile Video Streaming: Performance Analysis and Online Mechanism Design. - Lin Gao 001; Ming Tang 006; Haitian Pang; Jianwei Huang 001; Lifeng Sun (IEEE Trans. Mob. Comput., 2019)

Communication, Computation, and Caching Resource Sharing for the Internet of Things. - Ming Tang 006; Lin Gao 001; Jianwei Huang 001 (IEEE Commun. Mag., 2020)

An Incentive Mechanism for Cross-Silo Federated Learning: A Public Goods Perspective. - Ming Tang 006; Vincent W. S. Wong 001 (INFOCOM, 2021)

How Do You Earn Money on Live Streaming Platforms? - A Study of Donation-Based Markets. - Ming Tang 006; Jianwei Huang 001 (IEEE/ACM Trans. Netw., 2021)

Deep Reinforcement Learning for Task Offloading in Mobile Edge Computing Systems. - Ming Tang 006; Vincent W. S. Wong 001 (IEEE Trans. Mob. Comput., 2022)

Online Bitrate Selection for Viewport Adaptive 360-Degree Video Streaming. - Ming Tang 006; Vincent W. S. Wong 001 (IEEE Trans. Mob. Comput., 2022)

Caching for Edge Inference at Scale: A Mean Field Multi-Agent Reinforcement Learning Approach. - Yanqing Lu; Meng Zhang 013; Ming Tang 006 (GLOBECOM, 2023)

GNN-Based Neighbor Selection and Resource Allocation for Decentralized Federated Learning. - Chuiyang Meng; Ming Tang 006; Mehdi Setayesh; Vincent W. S. Wong 001 (GLOBECOM, 2023)

Tackling System Induced Bias in Federated Learning: Stratification and Convergence Analysis. - Ming Tang 006; Vincent W. S. Wong 001 (INFOCOM, 2023)

Multi-objective Deep Reinforcement Learning for Mobile Edge Computing. - Ning Yang 005; Junrui Wen; Meng Zhang 013; Ming Tang 006 (WiOpt, 2023)

Fractional Deep Reinforcement Learning for Age-Minimal Mobile Edge Computing. - Lyudong Jin; Ming Tang 006; Meng Zhang 013; Hao Wang (AAAI, 2024)

FedRC: A Rapid-Converged Hierarchical Federated Learning Framework in Street Scene Semantic Understanding. - Wei-Bin Kou; Qingfeng Lin; Ming Tang 006; Shuai Wang 004; Guangxu Zhu; Yik-Chung Wu (IROS, 2024)

Convergence Analysis of Split Federated Learning on Heterogeneous Data. - Pengchao Han; Chao Huang 028; Geng Tian; Ming Tang 006; Xin Liu 002 (CoRR, 2024)

Efficient Online Unlearning via Hessian-Free Recollection of Individual Data Statistics. - Xinbao Qiao; Meng Zhang 013; Ming Tang 006; Ermin Wei (CoRR, 2024)

PraFFL: A Preference-Aware Scheme in Fair Federated Learning. - Rongguang Ye; Ming Tang 006 (CoRR, 2024)

pFedLVM: A Large Vision Model (LVM)-Driven and Latent Feature-Based Personalized Federated Learning Framework in Autonomous Driving. - Wei-Bin Kou; Qingfeng Lin; Ming Tang 006; Sheng Xu; Rongguang Ye; Yang Leng; Shuai Wang 004; Zhenyu Chen; Guangxu Zhu; Yik-Chung Wu (CoRR, 2024)

An Adverse Weather-Immune Scheme with Unfolded Regularization and Foundation Model Knowledge Distillation for Street Scene Understanding. - Wei-Bin Kou; Guangxu Zhu; Rongguang Ye; Shuai Wang 004; Qingfeng Lin; Ming Tang 006; Yik-Chung Wu (CoRR, 2024)

Asynchronous Fractional Multi-Agent Deep Reinforcement Learning for Age-Minimal Mobile Edge Computing. - Lyudong Jin; Ming Tang 006; Jiayu Pan; Meng Zhang 013; Hao Wang (CoRR, 2024)

Promoting Collaboration in Cross-Silo Federated Learning: Challenges and Opportunities. - Chao Huang 028; Ming Tang 006; Qian Ma 002; Jianwei Huang 001; Xin Liu 002 (IEEE Commun. Mag., 2024)

A Blockchain-Empowered Incentive Mechanism for Cross-Silo Federated Learning. - Ming Tang 006; Fu Peng; Vincent W. S. Wong 001 (IEEE Trans. Mob. Comput., 2024)

Cloud-Edge-End Collaborative Task Offloading in Vehicular Edge Networks: A Multilayer Deep Reinforcement Learning Approach. - Jiaqi Wu; Ming Tang 006; Changkun Jiang; Lin Gao 001; Bin Cao 003 (IEEE Internet Things J., 2024)

Incentivizing Efficient Label Denoising in Federated Learning. - Yizhou Yan; Xinyu Tang; Chao Huang 028; Ming Tang 006 (IEEE Internet Things J., 2024)

One-for-All Pruning: A Universal Model for Customized Compression of Large Language Models. - Rongguang Ye; Ming Tang 006 (ACL (Findings), 2025)

Hessian-Free Online Certified Unlearning. - Xinbao Qiao; Meng Zhang 013; Ming Tang 006; Ermin Wei (ICLR, 2025)

PraFFL: A Preference-Aware Scheme in Fair Federated Learning. - Rongguang Ye; Wei-Bin Kou; Ming Tang 006 (KDD (1), 2025)

Enhancing Large Vision Model in Street Scene Semantic Understanding through Leveraging Posterior Optimization Trajectory. - Wei-Bin Kou; Qingfeng Lin; Ming Tang 006; Shuai Wang 004; Rongguang Ye; Guangxu Zhu; Yik-Chung Wu (CoRR, 2025)

Label Anything: An Interpretable, High-Fidelity and Prompt-Free Annotator. - Wei-Bin Kou; Guangxu Zhu; Rongguang Ye; Shuai Wang 004; Ming Tang 006; Yik-Chung Wu (CoRR, 2025)

Learning Heterogeneous Performance-Fairness Trade-offs in Federated Learning. - Rongguang Ye; Ming Tang 006 (CoRR, 2025)

FedEMA: Federated Exponential Moving Averaging with Negative Entropy Regularizer in Autonomous Driving. - Wei-Bin Kou; Guangxu Zhu; Bingyang Cheng; Shuai Wang 004; Ming Tang 006; Yik-Chung Wu (CoRR, 2025)

iMacSR: Intermediate Multi-Access Supervision and Regularization in Training Autonomous Driving Models. - Wei-Bin Kou; Guangxu Zhu; Yichen Jin; Shuai Wang 004; Ming Tang 006; Yik-Chung Wu (CoRR, 2025)

An Information-Theoretic Analysis for Federated Learning under Concept Drift. - Fu Peng; Meng Zhang 013; Ming Tang 006 (CoRR, 2025)

Fast-Convergent and Communication-Alleviated Heterogeneous Hierarchical Federated Learning in Autonomous Driving. - Wei-Bin Kou; Qingfeng Lin; Ming Tang 006; Rongguang Ye; Shuai Wang 004; Guangxu Zhu; Yik-Chung Wu (IEEE Trans. Intell. Transp. Syst., 2025)

Adverse Weather-Independent Framework Towards Autonomous Driving Perception through Temporal Correlation and Unfolded Regularization. - Wei-Bin Kou; Guangxu Zhu; Rongguang Ye; Jingreng Lei; Shuai Wang 004; Qingfeng Lin; Ming Tang 006; Yik-Chung Wu (CoRR, 2025)