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119 * Mon, 8/3/2020, 1:00 PM - 2:50 PM Virtual
Statistical Learning Applications for Autonomous Systems in Defense and National Security — Topic Contributed Papers
Section on Statistics in Defense and National Security, Section on Statistical Learning and Data Science, Section on Statistical Computing
Organizer(s): Joseph D Warfield, Johns Hopkins University Applied Physics Laboratory
Chair(s): Justin T Newcomer, Sandia National Laboratories
1:05 PM Tallis: A Statistical Approach for Dimension Reduction of Mixed-Type Variables
Alexander Foss, Sandia National Laboratories
1:25 PM Challenges in Test and Evaluation of AI-Enabled Systems in the DoD
Jane Pinelis, DoD Joint Artificial Intelligence Center
1:45 PM Multinomial Pattern Matching
John Richards, Sandia National Laboratories
2:05 PM Leveraging Machine Learning for Autonomy Testing and Evaluation
Galen Mullins, Johns Hopkins University Applied Physics Laboratory
2:25 PM Demystifying the Black Box: A Strategy for Testing AI-Enabled Systems
Heather Wojton, Institute for Defense Analyses; Daniel Porter, Institute for Defense Analyses
2:45 PM Floor Discussion