Machine Learning Integrity (MLI)
LAS research in Machine Learning Integrity seeks to address analytic integrity, quality, and assurance issues inherent within machine learning approaches. We specifically seek to demonstrate practical applications of machine learning integrity concepts such as data labeling alternatives and model explainability to address problems in cyber network defense and countering foreign influence campaigns and more broadly address big data triage and reasoning challenges via the creation and analysis of knowledge graphs.
- North Carolina State University Department of Computer Science
- East Carolina University Department of Political Science
For more information, please contact Ms. Lori Wachter – email@example.com