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.

MLI Performers

For more information, please contact Ms. Lori Wachter –

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LAS aims to bring together a multi-disciplinary group of academic, industry, and government researchers, analysts and managers together to re-engineer the intelligence analysis process to promote predictive analysis. LAS will do this by conducting both classified and unclassified research in a variety of areas of research. The research done in this area will serve as the foundation for mission effects and integrated back into the enterprise.

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