Publications

This page shows my publications chronologically. You can also find them on my Google Scholar.

Conference

1. Jingdi Chen, Hanhan Zhou, Yongsheng Mei, Carlee Joe-Wong, Gina Adam, Nathaniel D. Bastian, Tian Lan. RGMDT: Return-Gap-Minimizing Decision Tree Extraction in Non-Euclidean Metric Space, Conference on Neural Information Processing Systems (NeurIPS), December 2024. [PDF]
2. Hanhan Zhou, Jingdi Chen, Yongsheng Mei, Gina Adam, Vaneet Aggarwal, Nathaniel D. Bastian, and Tian Lan. Real-time Network Intrusion Detection via Importance Sampled Decision Transformers, Invited Paper, In Proceedings of the 21st IEEE International Conference on Mobile Ad Hoc and Smart Systems (MASS), September 2024. [PDF]
3. Kailash Gogineni, Yongsheng Mei, Karthikeya Gogineni, Peng Wei, Tian Lan, Guru Venkataramani, Characterizing and Optimizing the End-to-End Performance of Multi-Agent Reinforcement Learning Systems, IEEE International Symposium on Workload Characterization (ISWC), August 2024. [PDF]
4. Yongsheng Mei, Mahdi Imani, and Tian Lan, Bayesian Optimization through Gaussian Cox Process Models for Spatio-temporal Data, International Conference on Learning Representations (ICLR), May 2024. [PDF][BibTeX]
5. Yongsheng Mei, Hanhan Zhou, and Tian Lan, Projection-Optimal Monotonic Value Function Factorization in Multi-Agent Reinforcement Learning, International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2024. [PDF][BibTex]
6. Jingdi Chen, Hanhan Zhou, Yongsheng Mei, Gina Adam, Nathaniel Bastian, and Tian Lan. Real-time Network Intrusion Detection via Decision Transformers, AAAI workshop on Artificial Intelligence for Cyber Security (AICS), February 2024. [PDF][BibTeX]
7. Yongsheng Mei, Tian Lan, Mahdi Imani, and Suresh Subramaniam, A Bayesian Optimization Framework for Finding Local Optima in Expensive Multi-Modal Functions, European Conference on Artificial Intelligence (ECAI), September 2023. [PDF][BibTeX]
8. Yongsheng Mei, Guru Venkataramani, and Tian Lan, Exploiting Partial Common Information Microstructure for Multi-Modal Brain Tumor Segmentation, ICML workshop on Machine Learning for Multimodal Healthcare Data (ML4MHD), July 2023. [PDF][BibTeX]
9. Kailash Gogineni, Yongsheng Mei, Peng Wei, Tian Lan, and Guru Venkataramani, AccMER: Accelerating Multi-agent Experience Replay with Cache Locality-aware Prioritization, IEEE International Conference on Application-specific Systems, Architectures, and Processors (ASAP), July 2023. [PDF][BibTeX]
10. Yongsheng Mei, Hanhan Zhou, Tian Lan, Guru Venkataramani, and Peng Wei, MAC-PO: Multi-Agent Experience Replay via Collective Priority Optimization, International Conference on Autonomous Agents and Multiagent Systems (AAMAS), June 2023. [PDF][BibTeX]
11. Kailash Gogineni, Yongsheng Mei, Guru Venkataramani, and Tian Lan, Verify-Pro: A Framework for Server Authentication Using Communication Protocol Dialects, IEEE Military Communications Conference (MILCOM), September 2022. [PDF][BibTeX]
12. Yongsheng Mei, Kailash Gogineni, Tian Lan, and Guru Venkataramani, MPD: Moving Target Defense through Communication Protocol Dialects, International Conference on Security and Privacy in Communication Networks (SecureComm), September 2021. [PDF][BibTeX]
13. Hongfa Xue, Yongsheng Mei, Kailash Gogineni, Guru Venkataramani, and Tian Lan, Twin-Finder: Integrated Reasoning Engine for Pointer-related Code Clone Detection, International Workshop on Software Clones (IWSC), February 2020. [PDF][BibTeX]

Journal

1. Jiayu Chen, Bhargav Ganguly, Yang Xu, Yongsheng Mei, Tian Lan, Vaneet Aggarwal, Deep Generative Models for Offline Policy Learning: Tutorial, Survey, and Perspectives on Future Directions, Transactions on Machine Learning Research (TMLR), August 2024. [PDF][BibTeX]
2. Yurong Chen, Yongsheng Mei, Tian Lan, and Guru Venkataramani, Exploring Effective Fuzzing Strategies to Analyze Communication Protocols, ACM Digital Threats: Research and Practice (DTRAP), March 2024. [PDF][BibTeX]

Preprint

1. Yongsheng Mei, Liangqi Yuan, Dong-Jun Han, Kevin S Chan, Christopher Brinton, and Tian Lan. Continual Federated Learning with Conditional Diffusion Models as Replay, May 2024. [PDF]