Stony Brook University 3 credits ESE
Introduction to convex optimization and its applications. Convex sets, functions, and basics of convex analysis. Linear and quadratic programs, second-order cone and semidefinite programming, geometric programming. Duality theory and optimality conditions. Unconstrained minimization methods. Interior-point methods. Nondifferentiable problems. Decomposition methods. Applications in engineering fields including statistical signal processing, communications, networking, energy systems, circuit design, and machine learning. 3 credits Grading Letter graded (A, A-, B+, etc.)
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