A Reusable Behavior Modeling Method Based on Atom Action and Atom Condition. - Yingqian Bao; Qingjun Qu; Yiping Yao; Jiawei Fei; Miao Zhang 037 (SimuTools, 2017)

A discrete PSO-based static load balancing algorithm for distributed simulations in a cloud environment. - Miao Zhang 037; Yong Peng 006; Mei Yang; Quanjun Yin; Xu Xie 005 (Future Gener. Comput. Syst., 2021)

A Review of Failure Prediction in Distributed Data Centers. - Yuqing Ma; Xu Xie 005; Miao Zhang 037 (AsiaSim (1), 2022)

FedHiSyn: A Hierarchical Synchronous Federated Learning Framework for Resource and Data Heterogeneity. - Guanghao Li; Yue Hu 016; Miao Zhang 037; Ji Liu 003; Quanjun Yin; Yong Peng 006; Dejing Dou (ICPP, 2022)

FedGosp: A Novel Framework of Gossip Federated Learning for Data Heterogeneity. - Guanghao Li; Yue Hu; Miao Zhang 037; Li Li 064; Tao Chang; Quanjun Yin (SMC, 2022)

SparseAdapter: An Easy Approach for Improving the Parameter-Efficiency of Adapters. - Shwai He; Liang Ding 006; Daize Dong; Miao Zhang 037; Dacheng Tao (CoRR, 2022)

Efficient Flow-Based Scheduling for Geo-Distributed Simulation Tasks in Collaborative Edge and Cloud Environments. - Miao Zhang 037; Yong Peng 006; Jiancheng Zhu; Quanjun Yin (IEEE Trans. Parallel Distributed Syst., 2022)

Credit-based Differential Privacy Stochastic Model Aggregation Algorithm for Robust Federated Learning via Blockchain. - Mengyao Du; Miao Zhang 037; Lin Liu 018; Kai Xu 014; Quanjun Yin (ICPP, 2023)

Deep Model Fusion: A Survey. - Weishi Li; Yong Peng 006; Miao Zhang 037; Liang Ding 006; Han Hu 003; Li Shen 008 (CoRR, 2023)

Asymmetrically Decentralized Federated Learning. - Qinglun Li; Miao Zhang 037; Nan Yin; Quanjun Yin; Li Shen 008 (CoRR, 2023)

The Risk of Federated Learning to Skew Fine-Tuning Features and Underperform Out-of-Distribution Robustness. - Mengyao Du; Miao Zhang 037; Yuwen Pu; Kai Xu 014; Shouling Ji; Quanjun Yin (CoRR, 2024)

OledFL: Unleashing the Potential of Decentralized Federated Learning via Opposite Lookahead Enhancement. - Qinglun Li; Miao Zhang 037; Mengzhu Wang; Quanjun Yin; Li Shen 008 (CoRR, 2024)

Boosting the Performance of Decentralized Federated Learning via Catalyst Acceleration. - Qinglun Li; Miao Zhang 037; Yingqi Liu; Quanjun Yin; Li Shen 008; Xiaochun Cao (CoRR, 2024)

Low-Cost, High-Reliability Deployment for Cloud Applications With Low-Frequency Periodic Requests. - Hailiang Chen; Zhu Xiang; Lujia Yin; Miao Zhang 037; Quanjun Yin (IEEE Trans. Serv. Comput., 2024)

AgentDropout: Dynamic Agent Elimination for Token-Efficient and High-Performance LLM-Based Multi-Agent Collaboration. - Zhexuan Wang; Yutong Wang; Xuebo Liu 002; Liang Ding 006; Miao Zhang 037; Jie Liu 001; Min Zhang 005 (ACL (1), 2025)

Multi-agent reinforcement learning for task offloading with hybrid decision space in multi-access edge computing. - Ji Wang; Miao Zhang 037; Quanjun Yin; Lujia Yin; Yong Peng 006 (Ad Hoc Networks, 2025)

DFedGFM: Pursuing global consistency for Decentralized Federated Learning via global flatness and global momentum. - Qinglun Li; Miao Zhang 037; Tao Sun 005; Quanjun Yin; Li Shen 008 (Neural Networks, 2025)

Asymmetrically Decentralized Federated Learning. - Qinglun Li; Miao Zhang 037; Nan Yin; Quanjun Yin; Li Shen 008; Xiaochun Cao (IEEE Trans. Computers, 2025)

The Risk of Federated Learning to Skew Fine-Tuning Features and Underperform Robustness. - Mengyao Du; Miao Zhang 037; Yuwen Pu; Qingming Li; Shouling Ji; Quanjun Yin (IEEE Trans. Neural Networks Learn. Syst., 2025)