Research focus
About the research
Machine learning becomes more useful when people can interact with it and understand its reasoning.
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Bilgic directs the Machine Learning Laboratory, studying active learning, interactive learning, and explainable AI. His interests include learning from rationales, probabilistic graphical models, and statistical relational learning. The group also investigates interpretability, robustness, and model stability. This research connects the way a system acquires information with the way its predictions can be examined, addressing questions about how human feedback and structured relationships contribute to learning.
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