| Re-animator: Versatile high-fidelity storage-system tracing and replaying IU Akgun, G Kuenning, E Zadok Proceedings of the 13th ACM International Systems and Storage Conference, 61-74, 2020 | 21 | 2020 |
| A machine learning framework to improve storage system performance IU Akgun, AS Aydin, A Shaikh, L Velikov, E Zadok Proceedings of the 13th ACM Workshop on Hot Topics in Storage and File …, 2021 | 18 | 2021 |
| Improving storage systems using machine learning IU Akgun, AS Aydin, A Burford, M McNeill, M Arkhangelskiy, E Zadok ACM Transactions on Storage 19 (1), 1-30, 2023 | 12 | 2023 |
| KMLib: Towards Machine Learning for Operating Systems IU Akgun, AS Aydin, E Zadok On-device Intelligence Workshop MLSys 2020, 2020 | 6 | 2020 |
| Kml: Using machine learning to improve storage systems IU Akgun, AS Aydin, A Burford, M McNeill, M Arkhangelskiy, A Shaikh, ... arXiv preprint arXiv:2111.11554, 2021 | 3 | 2021 |
| Using Machine Learning to Improve Operating Systems' I/O Subsystems IU Akgun State University of New York at Stony Brook, 2022 | 1 | 2022 |
| Performance evaluation of unfolded sparse matrix-vector multiplication İÜ Akgün Master thesis, Ozyegin University, 2015 | 1 | 2015 |
| Predicting Network Buffer Capacity for BBR Fairness IU Akgun, S Vargas, M Arkhangelskiy, A Burford, M McNeill, ... NeurIPS MLSys Workshop, 2022 | | 2022 |
| Re-Animator: Versatile High-Fidelity System-Call Tracing and Replaying IU Akgun | | 2019 |
Erez ZadokProfessor of Computer Science, Stony Brook University在 cs.stonybrook.edu 的电子邮件经过验证
