Explore advanced concepts in generalization theory with renowned experts Peter Bartlett from UC Berkeley and Sasha Rakhlin from MIT in this 1-hour 18-minute lecture from the Deep Learning Boot Camp at the Simons Institute. Delve into cutting-edge research and insights on the third installment of the generalization series, gaining valuable knowledge on how machine learning models perform on unseen data and the theoretical foundations behind their ability to generalize.
Overview
Syllabus
Generalization III
Taught by
Simons Institute
Related Courses
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Generalization I
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Generalization II
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Launching into Machine Learning
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Machine Learning with Python: from Linear Models to Deep Learning.
3.0 -
Prediction, Generalization, and Complexity: Classical Statistical Theory Revisited - Part 1
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Modern Paradigms of Generalization - The Heliocentric Model of Aristarchus
