These issues present several grand challenges for ML that are the Center’s research foci:

Adding to these challenges are the need to fuse information from multiple sensors, adapt to dynamic environments, cope with missing or severely corrupted data, design more efficient ML hardware, and combat adversarial forces aiming to disrupt ML systems. Furthermore, the decision-making mechanisms of existing ML systems are often difficult to interpret, calling into question the use of such systems in mission-critical operations. This issue has limited the impact of state-of-the-art ML theory and methods in specialized applications. Many application domains may not be so well-defined and, while data rich, they tend to be label poor. ML has advanced considerably in recent years, but mostly in well-defined domains using huge amounts of human-labeled training data. The Center is developing the next-generation of Machine Learning (ML) theory, algorithms, and applications. The MADLab is a University Center of Excellence supported by the Air Force Office of Scientific Research (AFOSR) and the Air Force Research Lab (AFRL).

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