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Preview of Knowing When You Don’t Know: Quantifying and Reasoning about Uncertainty in Machine Learning Models

November 2022 Video
Eric Heim

This short video provides an introduction to a research topic presented at the SEI Research Review 2022.

Publisher:

Software Engineering Institute

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Abstract

Dr. Eric Heim previews his CMU SEI Research Review 2022 presentation on Uncertainty Machine Learning Techniques. The full presentation about this research project will be broadcast to registered attendees on Monday, November 14, 2022 at 1:00 PM ET. Visit https://resources.sei.cmu.edu/news-events/events/research-review/index.cfm to register for the November 14-16, 2022 event.

At the 2022 Research Review, our researchers will detail how they are forging a new path for software engineering by executing the SEI’s technical strategy to deliver tangible results. They will highlight methods, prototypes, and tools aimed at the most important problems facing the DoD, industry, and academia, including AI engineering, computing at the tactical edge, threat hunting, continuous integration/continuous delivery, and machine learning trustworthiness. You will learn how our researchers' work in areas such as model-based system engineering, DevSecOps, automated design conformance, software/cyber/AI integration, and AI network defense—to name a few—has produced value for the U.S. Department of Defense (DoD) and advanced the state of the practice.