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Special Topics in Data and Information Science: Optimization for Machine Learning

ECE 539/COS 512

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The course is a graduate level course, focusing on the optimization theory (algorithms and complexity analysis) that arise in machine learning. It covers topics such as convex/nonconvex optimization, gradient methods, accelerations, stochastic algorithms, variance reduction, minimax optimization, etc. The course is proof-based, and mathematical oriented. A similar version of this course has been previously given by Prof. Elad Hazan in CS department in Spring 2019.
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Section L01

  • Type: Lecture
  • Section: L01
  • Status: O
  • Enrollment: 13
  • Capacity: 50
  • Class Number: 22818
  • Schedule: TTh 09:30 AM-10:50 AM