EC ENGR 236B
Convex Optimization
Electrical and Computer Engineering · 4 units · Graduate courses (200-299)
Introduction to convex optimization and its applications. Convex sets, functions, and basics of convex analysis. Convex optimization problems (linear and quadratic programming, second-order cone and semidefinite programming, geometric programming). Lagrange duality and optimality conditions. Applications of convex optimization. Unconstrained minimization methods. Interior-point and cutting-plane algorithms. Introduction to nonlinear programming.
Letter grading.
When it runs
Checking the Schedule of Classes…
Requisites
Official UCLA wording
Requisite: course 236A.
BruinTree reads · Prerequisite
confidence 1.00 · from textRequires
Everything that has to come before this course, not just the courses named in the requisite above.
EC ENGR 236B
- EC ENGR 236ALinear Programming
- MATH 115ALinear Algebra
1 direct requisite. Showing 3 courses over 3 levels; the branches marked with a count carry on past it. Every course here opens its own tree.
Unlocks
What this course is a requisite for, and what those courses lead to in turn.
EC ENGR 236B
- EC ENGR 236COptimization Methods for Large-Scale Systems
- EC ENGR M237Dynamic Programming
- CH ENGR 284AOptimization in Vector Spaces
- MECH&AE M276Dynamic Programming
4 courses list this as a requisite. The whole downstream is here — 4 courses over 1 level. Every course here opens its own tree.