Large-Scale Convex Optimization: Algorithms and Analyses via Monotone Operators

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Course Description

This course presents a unified analysis of large-scale convex optimization algorithms through the abstraction of monotone operators. The topics include monotone operators, primal-dual methods, randomized coordinate update methods, ADMM-type methods, maximality, duality, acceleration, scaled relative graphs, and distributed and decentralized optimization

Grading Basis

ROP - Letter or Credit/No Credit

Min

3

Max

3

Course Repeatable for Degree Credit?

No

Course Component

Lecture

Enrollment Optional?

No

Programs

EE392F is a completion requirement for:
  • (from the following course set: )
  • (from the following course set: )