4 citations · 4 across the 9 of their papers we have counts for
5 papers · 1 filter
Green Runner: A tool for efficient deep learning component selection
Jai Kannan
For software that relies on machine-learned functionality, model selection is key to finding the right model for the task with desired performance characteristics. Evaluating a mod…
MLGuard: Defend Your Machine Learning Model!
Sheng Wong, Scott Barnett, Jessica Rivera-Villicana +4
Machine Learning (ML) is used in critical highly regulated and high-stakes fields such as finance, medicine, and transportation. The correctness of these ML applications is importa…
Green Runner: A tool for efficient model selection from model repositories
Jai Kannan, Scott Barnett, Anj Simmons +2
Deep learning models have become essential in software engineering, enabling intelligent features like image captioning and document generation. However, their popularity raises co…
Comparative analysis of real bugs in open-source Machine Learning projects -- A Registered Report
Tuan Dung Lai, Anj Simmons, Scott Barnett +2
Background: Machine Learning (ML) systems rely on data to make predictions, the systems have many added components compared to traditional software systems such as the data process…
MLSmellHound: A Context-Aware Code Analysis Tool
Jai Kannan, Scott Barnett, Luís Cruz +2
Meeting the rise of industry demand to incorporate machine learning (ML) components into software systems requires interdisciplinary teams contributing to a shared code base. To ma…