| Tifl: A tier-based federated learning system Z Chai, A Ali, S Zawad, S Truex, A Anwar, N Baracaldo, Y Zhou, H Ludwig, ... Proceedings of the 29th international symposium on high-performance parallel …, 2020 | 342 | 2020 |
| FedAT: A high-performance and communication-efficient federated learning system with asynchronous tiers Z Chai, Y Chen, A Anwar, L Zhao, Y Cheng, H Rangwala Proceedings of the International Conference for High Performance Computing …, 2021 | 153 | 2021 |
| Fedat: A communication-efficient federated learning method with asynchronous tiers under non-iid data Z Chai, Y Chen, L Zhao, Y Cheng, H Rangwala ArXivorg, 2020 | 115 | 2020 |
| Towards taming the resource and data heterogeneity in federated learning Z Chai, H Fayyaz, Z Fayyaz, A Anwar, Y Zhou, N Baracaldo, H Ludwig, ... 2019 USENIX conference on operational machine learning (OpML 19), 19-21, 2019 | 98 | 2019 |
| Characterizing co-located datacenter workloads: An alibaba case study Y Cheng, Z Chai, A Anwar Proceedings of the 9th asia-pacific workshop on systems, 1-3, 2018 | 86 | 2018 |
| Beyond efficiency: A systematic survey of resource-efficient large language models G Bai, Z Chai, C Ling, S Wang, J Lu, N Zhang, T Shi, Z Yu, M Zhu, ... arXiv preprint arXiv:2401.00625, 2024 | 73 | 2024 |
| Asynchronous federated learning for sensor data with concept drift Y Chen, Z Chai, Y Cheng, H Rangwala 2021 IEEE International Conference on Big Data (Big Data), 4822-4831, 2021 | 48 | 2021 |
| Federated multi-task learning with hierarchical attention for sensor data analytics Y Chen, Y Ning, Z Chai, H Rangwala 2020 International Joint Conference on Neural Networks (IJCNN), 1-8, 2020 | 31 | 2020 |
| Toward model parallelism for deep neural network based on gradient-free ADMM framework J Wang, Z Chai, Y Cheng, L Zhao 2020 IEEE International Conference on Data Mining (ICDM), 591-600, 2020 | 23 | 2020 |
| Toward quantized model parallelism for graph-augmented mlps based on gradient-free admm framework J Wang, H Li, Z Chai, Y Wang, Y Cheng, L Zhao IEEE Transactions on Neural Networks and Learning Systems 35 (4), 4491-4501, 2022 | 8 | 2022 |
| Federated multi-task hierarchical attention model for sensor analytics Y Chen, Y Ning, Z Chai, H Rangwala arXiv preprint arXiv:1905.05142, 2019 | 5 | 2019 |
| Distributed graph neural network training with periodic historical embedding synchronization Z Chai, G Bai, L Zhao, Y Cheng arXiv preprint arXiv:2206.00057, 1-20, 2022 | 4 | 2022 |
| Staleness-Alleviated Distributed GNN Training via Online Dynamic-Embedding Prediction G Bai, Z Yu, Z Chai, Y Cheng, L Zhao arXiv preprint arXiv:2308.13466, 2023 | 3 | 2023 |
| Tunable subnetwork splitting for model-parallelism of neural network training J Wang, Z Chai, Y Cheng, L Zhao arXiv preprint arXiv:2009.04053, 2020 | 3 | 2020 |
| Distributed Graph Neural Network Training with Periodic Stale Representation Synchronization Z Chai, G Bai, L Zhao, Y Cheng | 1 | 2022 |
| FedAT: A high-performance and communication-efficient federated learning system with asynchronous tiers Z Chai, Y Chen, A Anwar, L Zhao, Y Cheng, H Rangwala Proceedings of the International Conference for High Performance Computing …, 2021 | | 2021 |
