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Explore a thought-provoking lecture by Sanmi Koyejo from Stanford University that delves into the relationship between generalization and accuracy in machine learning. Examine the concept of robust generalization and its implications for emerging generalization settings. Gain insights into new perspectives on this critical topic in artificial intelligence and data science. Discover how this research contributes to the ongoing discourse on machine learning model performance and reliability.
Syllabus
Does generalization imply accuracy on the line? A new look at robust generalization
Taught by
Simons Institute