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: )