| FA2: Fast, accurate autoscaling for serving deep learning inference with SLA guarantees K Razavi, M Luthra, B Koldehofe, M Mühlhäuser, L Wang 2022 IEEE 28th Real-Time and Embedded Technology and Applications Symposium …, 2022 | 23 | 2022 |
| Reconciling high accuracy, cost-efficiency, and low latency of inference serving systems M Salmani, S Ghafouri, A Sanaee, K Razavi, M Mühlhäuser, J Doyle, ... Proceedings of the 3rd Workshop on Machine Learning and Systems, 78-86, 2023 | 12 | 2023 |
| Distributed DNN serving in the network data plane K Razavi, G Karlos, V Nigade, M Mühlhäuser, L Wang Proceedings of the 5th International Workshop on P4 in Europe, 67-70, 2022 | 11 | 2022 |
| Operator as a service: Stateful serverless complex event processing M Luthra, S Hennig, K Razavi, L Wang, B Koldehofe 2020 IEEE International Conference on Big Data (Big Data), 1964-1973, 2020 | 9 | 2020 |
| FA2: Fast, accurate autoscaling for serving deep learning inference with SLA guarantees. In 2022 IEEE 28th Real-Time and Embedded Technology and Applications Symposium (RTAS) K Razavi, M Luthra, B Koldehofe, M Mühlhäuser, L Wang IEEE, 146ś159. https://doi. org/10.1109/RTAS54340, 2022 | 7 | 2022 |
| Sponge: Inference Serving with Dynamic SLOs Using In-Place Vertical Scaling K Razavi, S Ghafouri, M Mühlhäuser, P Jamshidi, L Wang Proceedings of the 4th Workshop on Machine Learning and Systems, 184-191, 2024 | 3 | 2024 |
| IPA: Inference Pipeline Adaptation to Achieve High Accuracy and Cost-Efficiency S Ghafouri, K Razavi, M Salmani, A Sanaee, T Lorido-Botran, L Wang, ... arXiv preprint arXiv:2308.12871, 2023 | 3 | 2023 |
| Towards Democratic Computing M Mühlhäuser, N Alexopoulos, U Gropengießer, K Razavi, L Wang From Multimedia Communications to the Future Internet: Essays Dedicated to …, 2024 | | 2024 |
| A Tale of Two Scales: Reconciling Horizontal and Vertical Scaling for Inference Serving Systems K Razavi, M Salmani, M Mühlhäuser, B Koldehofe, L Wang arXiv preprint arXiv:2407.14843, 2024 | | 2024 |
| NetNN: Neural Intrusion Detection System in Programmable Networks K Razavi, SD Fard, G Karlos, V Nigade, M Mühlhäuser, L Wang IEEE ISCC 2024 (Second Best Paper Award), 2024 | | 2024 |
| Resource Efficient Inference Serving With SLO Guarantee K Razavi Technische Universität Darmstadt, 0 | | |
Max MühlhäuserProfessor of Computer Science, Technische Universität Darmstadt在 informatik.tu-darmstadt.de 的电子邮件经过验证
