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Deep Learning Theory

ORF 543

1232
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This course is an introduction to deep learning theory. Using tools from mathematics (e.g. probability, functional analysis, spectral asymptotics and combinatorics) as well as physics (e.g. effective field theory, the 1/n expansion, and the renormalization group) we cover topics in approximation theory, optimization, and generalization.
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Section L01

  • Type: Lecture
  • Section: L01
  • Status: O
  • Enrollment: 14
  • Capacity: 30
  • Class Number: 21595
  • Schedule: MW 09:00 AM-10:20 AM