EE 6353
CONVEX OPTIMIZATION FOR ENGINEERS.
University of Texas at Arlington · UGRD · Fall 2026
1 section
Catalog description
This course presents an overview of standard methods in convex optimization with applications to real-world problems from multiple areas of engineering and sciences including, signal processing, machine learning, control, networks, power system analysis, mechanical and aerospace, and circuit design. Course materials include advanced linear algebra, numerical algorithms, constrained and unconstrained optimization, duality theory, semidefinite programming, nonlinear and mixed-integer optimization, convex algebraic geometry, and several engineering applications.
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001
Availability not recently verifiedClass #texas_arlington_new-2608Fall 2026UGRD3 credits
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