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Explore the intersection of statistical physics and machine learning in this 28-minute lecture on the stochastic gradient descent algorithm. Delve into the theoretical foundations and practical applications of this optimization technique, examining its behavior through the lens of statistical mechanics. Gain insights into how concepts from physics can be applied to understand and improve machine learning algorithms, with a focus on the stochastic gradient descent method widely used in training neural networks and other models.
Syllabus
Pierfrancesco Urbani - Statistical Physics of Stochastic Gradient Descent [IPhT60]
Taught by
IPhT-TV