1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.DC2023
SuperServe: Fine-Grained Inference Serving for Unpredictable Workloads
Alind Khare, Dhruv Garg, Sukrit Kalra +3
The increasing deployment of ML models on the critical path of production applications in both datacenter and the edge requires ML inference serving systems to serve these models u…
cs.CR2023★ 1 cited
Pareto-Secure Machine Learning (PSML): Fingerprinting and Securing Inference Serving Systems
Debopam Sanyal, Jui-Tse Hung, Manav Agrawal +6
Model-serving systems have become increasingly popular, especially in real-time web applications. In such systems, users send queries to the server and specify the desired performa…