Miao Zhang

According to our database, Miao Zhang authored at least 19 papers between 2017 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

The Risk of Federated Learning to Skew Fine-Tuning Features and Underperform Robustness.

Mengyao Du, Miao Zhang, Yuwen Pu, Qingming Li, Shouling Ji, Quanjun Yin

IEEE Trans. Neural Networks Learn. Syst., October, 2025

Asymmetrically Decentralized Federated Learning.

Qinglun Li, Miao Zhang, Nan Yin, Quanjun Yin, Li Shen, Xiaochun Cao

IEEE Trans. Computers, August, 2025

DFedGFM: Pursuing global consistency for Decentralized Federated Learning via global flatness and global momentum.

Qinglun Li, Miao Zhang, Tao Sun, Quanjun Yin, Li Shen

Neural Networks, 2025

Multi-agent reinforcement learning for task offloading with hybrid decision space in multi-access edge computing.

Ji Wang, Miao Zhang, Quanjun Yin, Lujia Yin, Yong Peng

Ad Hoc Networks, 2025

AgentDropout: Dynamic Agent Elimination for Token-Efficient and High-Performance LLM-Based Multi-Agent Collaboration.

Zhexuan Wang, Yutong Wang, Xuebo Liu, Liang Ding, Miao Zhang, Jie Liu, Min Zhang

Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

2024

Low-Cost, High-Reliability Deployment for Cloud Applications With Low-Frequency Periodic Requests.

Hailiang Chen, Zhu Xiang, Lujia Yin, Miao Zhang, Quanjun Yin

IEEE Trans. Serv. Comput., 2024

Boosting the Performance of Decentralized Federated Learning via Catalyst Acceleration.

Qinglun Li, Miao Zhang, Yingqi Liu, Quanjun Yin, Li Shen, Xiaochun Cao

CoRR, 2024

OledFL: Unleashing the Potential of Decentralized Federated Learning via Opposite Lookahead Enhancement.

Qinglun Li, Miao Zhang, Mengzhu Wang, Quanjun Yin, Li Shen

CoRR, 2024

The Risk of Federated Learning to Skew Fine-Tuning Features and Underperform Out-of-Distribution Robustness.

Mengyao Du, Miao Zhang, Yuwen Pu, Kai Xu, Shouling Ji, Quanjun Yin

CoRR, 2024

2023

Asymmetrically Decentralized Federated Learning.

Qinglun Li, Miao Zhang, Nan Yin, Quanjun Yin, Li Shen

CoRR, 2023

Deep Model Fusion: A Survey.

Weishi Li, Yong Peng, Miao Zhang, Liang Ding, Han Hu, Li Shen

CoRR, 2023

Credit-based Differential Privacy Stochastic Model Aggregation Algorithm for Robust Federated Learning via Blockchain.

Mengyao Du, Miao Zhang, Lin Liu, Kai Xu, Quanjun Yin

Proceedings of the 52nd International Conference on Parallel Processing, 2023

2022

Efficient Flow-Based Scheduling for Geo-Distributed Simulation Tasks in Collaborative Edge and Cloud Environments.

Miao Zhang, Yong Peng, Jiancheng Zhu, Quanjun Yin

IEEE Trans. Parallel Distributed Syst., 2022

SparseAdapter: An Easy Approach for Improving the Parameter-Efficiency of Adapters.

Shwai He, Liang Ding, Daize Dong, Miao Zhang, Dacheng Tao

CoRR, 2022

FedGosp: A Novel Framework of Gossip Federated Learning for Data Heterogeneity.

Guanghao Li, Yue Hu, Miao Zhang, Li Li, Tao Chang, Quanjun Yin

Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, 2022

FedHiSyn: A Hierarchical Synchronous Federated Learning Framework for Resource and Data Heterogeneity.

Guanghao Li, Yue Hu, Miao Zhang, Ji Liu, Quanjun Yin, Yong Peng, Dejing Dou

Proceedings of the 51st International Conference on Parallel Processing, 2022

A Review of Failure Prediction in Distributed Data Centers.

Yuqing Ma, Xu Xie, Miao Zhang

Proceedings of the Methods and Applications for Modeling and Simulation of Complex Systems, 2022

2021

A discrete PSO-based static load balancing algorithm for distributed simulations in a cloud environment.

Miao Zhang, Yong Peng, Mei Yang, Quanjun Yin, Xu Xie

Future Gener. Comput. Syst., 2021

2017

A Reusable Behavior Modeling Method Based on Atom Action and Atom Condition.

Yingqian Bao, Qingjun Qu, Yiping Yao, Jiawei Fei, Miao Zhang

Proceedings of the 10th EAI International Conference on Simulation Tools and Techniques, 2017