Special Topics in Data and Information Science: Optimization for Machine Learning
ECE 539/COS 512
1252
1252
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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: 29
- Capacity: 50
- Class Number: 22818
- Schedule: TTh 09:30 AM-10:50 AM - Engineering Quad B-Wing B205