Workshop paper
Towards Automating the AI Operations Lifecycle
Matthew Arnold, Jeffrey Boston, et al.
MLSys 2020
Machine-learning operators often have correctness constraints that cut across multiple hyperparameters and/or data. Violating these constraints causes runtime exceptions, but they are usually documented only informally or not at all. This paper presents a verification-condition analysis for Python code. We demonstrate our analysis by extracting hyperparameter constraints for 45 sklearn operators. Our analysis is a step towards safer and more robust machine learning.
Matthew Arnold, Jeffrey Boston, et al.
MLSys 2020
Kahini Wadhawan, Payel Das, et al.
ICLR 2021
Shiqiang Wang, Nathalie Baracaldo Angel, et al.
NeurIPS 2022
Amit Alfassy, Assaf Arbelle, et al.
NeurIPS 2022