| Applying deep learning to the cache replacement problem Z Shi, X Huang, A Jain, C Lin Proceedings of the 52nd Annual IEEE/ACM International Symposium on …, 2019 | 172 | 2019 |
| A Hierarchical Neural Model of Data Prefetching Z Shi, A Jain, K Swersky, M Hashemi, P Ranganathan, C Lin The International Conference on Architectural Support for Programming …, 2021 | 93 | 2021 |
| Learning Execution through Neural Code Fusion Z Shi, K Swersky, D Tarlow, P Ranganathan, M Hashemi The International Conference on Learning Representations (ICLR), 2020 | 37 | 2020 |
| Deep embedding for determining the number of clusters Y Wang, Z Shi, X Guo, X Liu, E Zhu, J Yin Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 28 | 2018 |
| Harmony: Heterogeneity-aware hierarchical management for federated learning system C Tian, L Li, Z Shi, J Wang, CZ Xu 2022 55th IEEE/ACM International Symposium on Microarchitecture (MICRO), 631-645, 2022 | 22 | 2022 |
| Learned hardware/software co-design of neural accelerators Z Shi, C Sakhuja, M Hashemi, K Swersky, C Lin arXiv preprint arXiv:2010.02075, 2020 | 17 | 2020 |
| Leveraging domain information for the efficient automated design of deep learning accelerators C Sakhuja, Z Shi, C Lin 2023 IEEE International Symposium on High-Performance Computer Architecture …, 2023 | 15 | 2023 |
| HydraLoRA: An Asymmetric LoRA Architecture for Efficient Fine-Tuning C Tian, Z Shi, Z Guo, L Li, C Xu arXiv preprint arXiv:2404.19245, 2024 | 11 | 2024 |
| Proxyqa: An alternative framework for evaluating long-form text generation with large language models H Tan, Z Guo, Z Shi, L Xu, Z Liu, Y Feng, X Li, Y Wang, L Shang, Q Liu, ... arXiv preprint arXiv:2401.15042, 2024 | 8 | 2024 |
| Using bayesian optimization for hardware/software co-design of neural accelerators Z Shi, C Sakhuja, M Hashemi, K Swersky, C Lin Workshop on ML for Systems at the Conference on Neural Information …, 2020 | 8 | 2020 |
| A Neural Hierarchical Sequence Model for Irregular Data Prefetching Z Shi, A Jain, K Swersky, M Hashemi, P Ranganathan, C Lin ML for Systems Workshop at NeurIPS 2019, 2019 | 5 | 2019 |
| Learn to select: Efficient cross-device federated learning via reinforcement learning C Tian, Z Shi, L Li | 4 | 2023 |
| Ranking-based Client Imitation Selection for Efficient Federated Learning C Tian, Z Shi, L Li, C Xu Forty-first International Conference on Machine Learning, 0 | 3 | |
| Learning execution through neural code fusion S Zhan, S Kevin, T Daniel, R Parthasarathy, H Milad arXiv preprint arXiv:1906.07181, 2019 | 2 | 2019 |
| Ranking-based Client Selection with Imitation Learning for Efficient Federated Learning C Tian, Z Shi, X Qin, L Li, C Xu arXiv preprint arXiv:2405.04122, 2024 | 1 | 2024 |
| Machine learning for prediction problems in computer architecture Z Shi | | 2020 |
| POSTER: HARMONY: HETEROGENEITY-AWARE HIERARCHICAL MANAGEMENT FOR FEDERATED LEARNING SYSTEM C Tian, L Li, Z Shi, J Wang, CZ Xu | | |
Calvin LinProfessor of Computer Science, The University of Texas at AustinVerified email at cs.utexas.edu