## 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: Win, Sum
| Units: 3

Instructors:
Boyd, S. (PI)
;
Moehle, N. (PI)
;
Busseti, E. (TA)
;
Dao, T. (TA)
;
Fannjiang, C. (TA)
;
Go, K. (TA)
;
Hong, J. (TA)
;
Khosravi, K. (TA)
;
Lawson, D. (TA)
;
Lemon, A. (TA)
;
Li, C. (TA)
;
Tefagh, M. (TA)
;
Yu, J. (TA)
;
Zhechev, Z. (TA)

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