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
  • Section 01
    Abhishek Halder (ahalder)
    Shadi Haddad (shhaddad)
  • Section 01
    Abhishek Halder (ahalder)
    Kenneth Paulo Francisco Caluya (kcaluya)

Formerly AMS 0229

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