7 citations · 17 across the 5 of their papers we have counts for
5 papers
AI for Low-Code for AI
Nikitha Rao, Jason Tsay, Kiran Kate +2
Low-code programming allows citizen developers to create programs with minimal coding effort, typically via visual (e.g. drag-and-drop) interfaces. In parallel, recent AI-powered t…
Automatically Debugging AutoML Pipelines using Maro: ML Automated Remediation Oracle (Extended Version)
Julian Dolby, Jason Tsay, Martin Hirzel
Machine learning in practice often involves complex pipelines for data cleansing, feature engineering, preprocessing, and prediction. These pipelines are composed of operators, whi…
Comments on Comments: Where Code Review and Documentation Meet
Nikitha Rao, Jason Tsay, Martin Hirzel +1
A central function of code review is to increase understanding; helping reviewers understand a code change aids in knowledge transfer and finding bugs. Comments in code largely ser…
Enabling Reproducibility and Meta-learning Through a Lifelong Database of Experiments (LDE)
Jason Tsay, Andrea Bartezzaghi, Aleke Nolte +1
Artificial Intelligence (AI) development is inherently iterative and experimental. Over the course of normal development, especially with the advent of automated AI, hundreds or th…
Transparency and Coordination in Peer Production
Laura Dabbish, Colleen Stuart, Jason Tsay +1
This paper examines coordination in transparent work environments - environments where the content of work artifacts, and the actions taken on these artifacts, are fully visible to…