Hunting Garbage Collection Related Concurrency Bugs through Critical Condition Restoration. - Hanhan Zhou; Tian Lan 001; Guru Venkataramani (FEAST@CCS, 2020)

PT-VTON: an Image-Based Virtual Try-On Network with Progressive Pose Attention Transfer. - Hanhan Zhou; Tian Lan 001; Guru Venkataramani (CoRR, 2021)

PAC: Assisted Value Factorization with Counterfactual Predictions in Multi-Agent Reinforcement Learning. - Hanhan Zhou; Tian Lan 001; Vaneet Aggarwal (NeurIPS, 2022)

On the Convergence of Heterogeneous Federated Learning with Arbitrary Adaptive Online Model Pruning. - Hanhan Zhou; Tian Lan 001; Guru Venkataramani; Wenbo Ding 001 (CoRR, 2022)

PAC: Assisted Value Factorisation with Counterfactual Predictions in Multi-Agent Reinforcement Learning. - Hanhan Zhou; Tian Lan 001; Vaneet Aggarwal (CoRR, 2022)

MAC-PO: Multi-Agent Experience Replay via Collective Priority Optimization. - Yongsheng Mei; Hanhan Zhou; Tian Lan 001; Guru Venkataramani; Peng Wei (AAMAS, 2023)

Every Parameter Matters: Ensuring the Convergence of Federated Learning with Dynamic Heterogeneous Models Reduction. - Hanhan Zhou; Tian Lan 001; Guru Venkataramani; Wenbo Ding 001 (NeurIPS, 2023)

ReMIX: Regret Minimization for Monotonic Value Function Factorization in Multiagent Reinforcement Learning. - Yongsheng Mei; Hanhan Zhou; Tian Lan 001 (CoRR, 2023)

Two-tiered Online Optimization of Region-wide Datacenter Resource Allocation via Deep Reinforcement Learning. - Chang-Lin Chen; Hanhan Zhou; Jiayu Chen; Mohammad Pedramfar; Vaneet Aggarwal; Tian Lan 001; Zheqing Zhu; Chi Zhou; Tim Gasser; Pol Mauri Ruiz; Vijay Menon; Neeraj Kumar 004; et al. (CoRR, 2023)

Statistically Efficient Variance Reduction with Double Policy Estimation for Off-Policy Evaluation in Sequence-Modeled Reinforcement Learning. - Hanhan Zhou; Tian Lan 001; Vaneet Aggarwal (CoRR, 2023)

Real-time Network Intrusion Detection via Decision Transformers. - Jingdi Chen; Hanhan Zhou; Yongsheng Mei; Gina C. Adam; Nathaniel D. Bastian; Tian Lan 001 (CoRR, 2023)

Value Functions Factorization With Latent State Information Sharing in Decentralized Multi-Agent Policy Gradients. - Hanhan Zhou; Tian Lan 001; Vaneet Aggarwal (IEEE Trans. Emerg. Top. Comput. Intell., 2023)

ConcaveQ: Non-monotonic Value Function Factorization via Concave Representations in Deep Multi-Agent Reinforcement Learning. - Huiqun Li; Hanhan Zhou; Yifei Zou; Dongxiao Yu; Tian Lan 001 (AAAI, 2024)

Projection-Optimal Monotonic Value Function Factorization in Multi-Agent Reinforcement Learning. - Yongsheng Mei; Hanhan Zhou; Tian Lan 001 (AAMAS, 2024)

RGMDT: Return-Gap-Minimizing Decision Tree Extraction in Non-Euclidean Metric Space. - Jingdi Chen; Hanhan Zhou; Yongsheng Mei; Carlee Joe-Wong; Gina C. Adam; Nathaniel D. Bastian; Tian Lan 001 (NeurIPS, 2024)

Collaborative AI Teaming in Unknown Environments via Active Goal Deduction. - Zuyuan Zhang; Hanhan Zhou; Mahdi Imani; Taeyoung Lee; Tian Lan 001 (CoRR, 2024)

Learning to Collaborate with Unknown Agents in the Absence of Reward. - Zuyuan Zhang; Hanhan Zhou; Mahdi Imani; Taeyoung Lee; Tian Lan 001 (AAAI, 2025)

Learning-Based Two-Tiered Online Optimization of Region-Wide Datacenter Resource Allocation. - Chang-Lin Chen; Hanhan Zhou; Jiayu Chen; Mohammad Pedramfar; Tian Lan 001; Zheqing Zhu; Chi Zhou; Pol Mauri Ruiz; Neeraj Kumar 004; Hongbo Dong; Vaneet Aggarwal (IEEE Trans. Netw. Serv. Manag., 2025)

WHEN TO ACT, WHEN TO WAIT: Modeling Structural Trajectories for Intent Triggerability in Task-Oriented Dialogue. - Yaoyao Qian; Jindan Huang; Yuanli Wang; Simon Yu; Kyrie Zhixuan Zhou; Jiayuan Mao; Mingfu Liang; Hanhan Zhou (CoRR, 2025)