4 citations · 4 across the 9 of their papers we have counts for
9 papers
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…
Garbage in, garbage out: Zero-shot detection of crime using Large Language Models
Anj Simmons, Rajesh Vasa
This paper proposes exploiting the common sense knowledge learned by large language models to perform zero-shot reasoning about crimes given textual descriptions of surveillance vi…
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…
SignalKG: Towards Reasoning about the Underlying Causes of Sensor Observations
Anj Simmons, Rajesh Vasa, Antonio Giardina
This paper demonstrates our vision for knowledge graphs that assist machines to reason about the cause of signals observed by sensors. We show how the approach allows for construct…
Signal Knowledge Graph
Anj Simmons, Rajesh Vasa
This paper presents an knowledge graph to assist in reasoning over signals for intelligence purposes. We highlight limitations of existing knowledge graphs and reasoning systems fo…
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…
A reliability measure for smart surveillance systems
Anj Simmons
We present a reliability measure for smart surveillance systems, taking into account the adversarial nature of intrusion. Our approach is based on percolation theory and is a gener…