4 citations · 5 across the 2 of their papers we have counts for
4 papers
Learning Prediction Intervals for Model Performance
Benjamin Elder, Matthew Arnold, Anupama Murthi +1
Understanding model performance on unlabeled data is a fundamental challenge of developing, deploying, and maintaining AI systems. Model performance is typically evaluated using te…
Not Your Grandfathers Test Set: Reducing Labeling Effort for Testing
Begum Taskazan, Jiri Navratil, Matthew Arnold +3
Building and maintaining high-quality test sets remains a laborious and expensive task. As a result, test sets in the real world are often not properly kept up to date and drift fr…
Towards Automating the AI Operations Lifecycle
Matthew Arnold, Jeffrey Boston, Michael Desmond +5
Today's AI deployments often require significant human involvement and skill in the operational stages of the model lifecycle, including pre-release testing, monitoring, problem di…
Exploring the Hyperparameter Landscape of Adversarial Robustness
Evelyn Duesterwald, Anupama Murthi, Ganesh Venkataraman +2
Adversarial training shows promise as an approach for training models that are robust towards adversarial perturbation. In this paper, we explore some of the practical challenges o…