AM229: Convex Optimization

Focuses on recognizing, formulating, analyzing, and solving convex optimization problems encountered across science and engineering. Topics include: convex sets; convex functions; convex optimization problems; duality; subgradient calculus; algorithms for smooth and non-smooth convex optimization; applications to signal and image processing, machine learning, statistics, control, robotics and economics. Students are required to have knowledge of calculus and linear algebra, and exposure to probability.

5 credits

Year	Fall	Winter	Spring	Summer
2022-23	Section 01 Abhishek Halder (ahalder) Shadi Haddad (shhaddad)
2020-21	Section 01 Abhishek Halder (ahalder) Kenneth Paulo Francisco Caluya (kcaluya)

Comments

Formerly AMS 0229

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