## CME 364A: Convex Optimization I (CS 334A, EE 364A)

Convex sets, functions, and optimization problems. The basics of convex analysis and theory of convex programming: optimality conditions, duality theory, theorems of alternative, and applications. Least-squares, linear and quadratic programs, semidefinite programming, and geometric programming. Numerical algorithms for smooth and equality constrained problems; interior-point methods for inequality constrained problems. Applications to signal processing, communications, control, analog and digital circuit design, computational geometry, statistics, machine learning, and mechanical engineering. Prerequisite: linear algebra such as
EE263, basic probability.

Terms: Spr, Sum
| Units: 3

Instructors:
Angeris, G. (PI)
;
Boyd, S. (PI)
;
Momeni, A. (PI)
;
Agrawal, A. (TA)
;
Alexandari, A. (TA)
;
Fu, R. (TA)
;
Hemmati, S. (TA)
;
Lim, R. (TA)
;
Momeni, A. (TA)
;
Sharafat, A. (TA)
;
Sheng, H. (TA)
;
Sun, Q. (TA)
;
Yu, G. (TA)
;
Zaidi, M. (TA)
;
Zhang, J. (TA)

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