2 citations · 3 across the 3 of their papers we have counts for
3 papers
VirnyFlow: Optimizing ML Pipelines for Accuracy, Fairness, and Stability at Scale
Denys Herasymuk, Anastasiia Mozghova, Nazar Protsiv +2
Developing machine learning (ML) systems for real-world deployment requires navigating context-dependent trade-offs among accuracy, fairness, stability, and other objectives. Exist…
Still More Shades of Null: An Evaluation Suite for Responsible Missing Value Imputation
Falaah Arif Khan, Denys Herasymuk, Nazar Protsiv +1
Data missingness is a practical challenge of sustained interest to the scientific community. In this paper, we present Shades-of-Null, an evaluation suite for responsible missing v…
An Epistemic and Aleatoric Decomposition of Arbitrariness to Constrain the Set of Good Models
Falaah Arif Khan, Denys Herasymuk, Nazar Protsiv +1
Recent research reveals that machine learning (ML) models are highly sensitive to minor changes in their training procedure, such as the inclusion or exclusion of a single data poi…