| Towards federated learning with attention transfer to mitigate system and data heterogeneity of clients H Shi, V Radu Proceedings of the 4th international workshop on edge systems, analytics and …, 2021 | 11 | 2021 |
| Data selection for efficient model update in federated learning H Shi, V Radu Proceedings of the 2nd European Workshop on Machine Learning and Systems, 72-78, 2022 | 8 | 2022 |
| Distributed training for speech recognition using local knowledge aggregation and knowledge distillation in heterogeneous systems H Shi, V Radu, P Yang Proceedings of the 3rd Workshop on Machine Learning and Systems, 64-70, 2023 | 3 | 2023 |
| Lightweight Workloads in Heterogeneous Federated Learning via Few-shot Learning H Shi, V Radu, P Yang Proceedings of the 4th International Workshop on Distributed Machine …, 2023 | 1 | 2023 |
| Closing the gap between client and global model performance in heterogeneous federated learning H Shi, V Radu, P Yang arXiv preprint arXiv:2211.03457, 2022 | 1 | 2022 |
| Improving the participation of resource-constrained devices in federated learning H Shi University of Sheffield, 2025 | | 2025 |
| Federated Learning with Workload Reduction through Partial Training of Client Models and Entropy-Based Data Selection H Shi, V Radu, P Yang arXiv preprint arXiv:2501.00170, 2024 | | 2024 |
