| A survey of federated learning for edge computing: Research problems and solutions Q Xia, W Ye, Z Tao, J Wu, Q Li High-Confidence Computing 1 (1), 100008, 2021 | 167 | 2021 |
| {eSGD}: Communication efficient distributed deep learning on the edge Z Tao, Q Li USENIX Workshop on Hot Topics in Edge Computing (HotEdge 18), 2018 | 136 | 2018 |
| A survey of virtual machine management in edge computing Z Tao, Q Xia, Z Hao, C Li, L Ma, S Yi, Q Li Proceedings of the IEEE 107 (8), 1482-1499, 2019 | 114 | 2019 |
| FABA: an algorithm for fast aggregation against byzantine attacks in distributed neural networks Q Xia, Z Tao, Z Hao, Q Li IJCAI, 2019 | 57 | 2019 |
| Defenses against byzantine attacks in distributed deep neural networks Q Xia, Z Tao, Q Li IEEE Transactions on Network Science and Engineering 8 (3), 2025-2035, 2020 | 12 | 2020 |
| Qun Li Q Xia, W Ye, Z Tao, J Wu A survey of federated learning for edge computing: Research problems and …, 2021 | 10 | 2021 |
| Defending against byzantine attacks in quantum federated learning Q Xia, Z Tao, Q Li 2021 17th International Conference on Mobility, Sensing and Networking (MSN …, 2021 | 9 | 2021 |
| wpScalable Quantum Neural Networks for Classification J Wu, Z Tao, Q Li 2022 IEEE International Conference on Quantum Computing and Engineering (QCE …, 2022 | 8 | 2022 |
| An efficient and robust cloud-based deep learning with knowledge distillation Z Tao, Q Xia, S Chen, Q Li IEEE Transactions on Cloud Computing, 2022 | 6 | 2022 |
| Laws: Look around and warm-start natural gradient descent for quantum neural networks Z Tao, J Wu, Q Xia, Q Li 2023 IEEE International Conference on Quantum Software (QSW), 76-82, 2023 | 4 | 2023 |
| Privacy issues in edge computing Q Xia, Z Tao, Q Li Fog/Edge Computing For Security, Privacy, and Applications, 147-169, 2021 | 4 | 2021 |
| Byzantine Tolerant Algorithms for Federated Learning Q Xia, Z Tao, Q Li, S Chen IEEE Transactions on Network Science and Engineering, 2023 | 2 | 2023 |
| CE-SGD: Communication-Efficient Distributed Machine Learning Z Tao, Q Xia, Q Li, S Cheng 2021 IEEE Global Communications Conference (GLOBECOM), 1-7, 2021 | 2 | 2021 |
| Neuron manifold distillation for edge deep learning Z Tao, Q Xia, Q Li 2021 IEEE/ACM 29th International Symposium on Quality of Service (IWQOS), 1-10, 2021 | 2 | 2021 |
| A new perspective in understanding of Adam-Type algorithms and beyond Z Tao, Q Xia, Q Li | 1 | 2019 |
| Preconditioned Federated Learning Z Tao, J Wu, Q Li arXiv preprint arXiv:2309.11378, 2023 | | 2023 |
| High-Confidence Computing Q Xia, W Ye, Z Tao, J Wu, Q Li | | 2023 |
| Privacy-Preserving and Robust Federated Deep Metric Learning Y Tian, X Ke, Z Tao, S Ding, F Xu, Q Li, H Han, S Zhong, X Fu 2022 IEEE/ACM 30th International Symposium on Quality of Service (IWQoS), 1-11, 2022 | | 2022 |
| Communication and Computation Efficient Deep Learning Z Tao The College of William and Mary, 2022 | | 2022 |
| ToFi: An Algorithm to Defend Against Byzantine Attacks in Federated Learning Q Xia, Z Tao, Q Li Security and Privacy in Communication Networks: 17th EAI International …, 2021 | | 2021 |
