| Fedscale: Benchmarking model and system performance of federated learning at scale F Lai, Y Dai, S Singapuram, J Liu, X Zhu, H Madhyastha, M Chowdhury International conference on machine learning, 11814-11827, 2022 | 241 | 2022 |
| Efficient large language models: A survey Z Wan, X Wang, C Liu, S Alam, Y Zheng, Z Qu, S Yan, Y Zhu, Q Zhang, ... Transactions on Machine Learning Research, 2023 | 96 | 2023 |
| Fluid: Resource-aware Hyperparameter Tuning Engine P Yu*, J Liu*, M Chowdhury Proceedings of Machine Learning and Systems 3, 502-516, 2021 | 20 | 2021 |
| Auxo: Efficient Federated Learning via Scalable Client Clustering J Liu, F Lai, Y Dai, A Akella, H Madhyastha, M Chowdhury 14th edition of the annual ACM Symposium on Cloud Computing, 2023 | 16* | 2023 |
| Andes: Defining and Enhancing Quality-of-Experience in LLM-Based Text Streaming Services J Liu, Z Wu, JW Chung, F Lai, M Lee, M Chowdhury arXiv preprint arXiv:2404.16283, 2024 | 9 | 2024 |
| FedTrans: Efficient Federated Learning via Multi-Model Transformation Y Zhu, J Liu, M Chowdhury, F Lai Proceedings of Machine Learning and Systems 6, 395-407, 2024 | | 2024 |
| Venn: Resource Management Across Federated Learning Jobs J Liu, F Lai, D Ding, Y Zhang, M Chowdhury arXiv preprint arXiv:2312.08298, 2023 | | 2023 |
| IaC-Eval: A code generation benchmark for Infrastructure-as-Code programs PTJ Kon, J Liu, Y Qiu, W Fan, T He, L Lin, H Zhang, OM Park, ... | | |
Mosharaf ChowdhuryUniversity of MichiganPatvirtintas el. paštas umich.edu
