E0 350: Advanced Convex Optimization
Term: January - May 2023.
Credits: 3:1
Hours: Tuesday and Thursday, 10:00 - 11:30 hrs.
Instructor: Kunal Chaudhury. (kunal@iisc.ac.in)
Grading: project: 30% mid-term: 30%, final: 40%.
Prerequisites: linear algebra, basic multivariate calculus and optimization.
Topics: (theory) convex sets and functions, extended-real-valued convex functions, lower-semicontinuity, conjugate function, subgradient, subdifferential calculus, convex projection, supporting and separating hyperplane theorems, fixed-point iterations and convergence; proximal and averaged operators; (algorithms) gradient and subgradient descent, projected and proximal gradient descent, and ADMM.
Lecture notes: link.
References:
First-Order Methods in Optimization by Amir Beck.
Lectures on Convex Optimization by Yurii Nesterov.