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Convex Optimization


Stephen Boyd
Department of Management Science and Engineering Institute for Computational and Mathematical Engineering Stanford University
Course Type
Group 1
21-22-23-24 marzo 2011 10:00-13:00
This course will concentrate on recognizing and solving convex optimization problems that arise in engineering and related areas (e.g., machine learning, finance). Topics include convex sets, functions, and optimization problems; basics of convex analysis; least-squares, linear and quadratic programs, geometric and semidefinite programming; optimality conditions, duality theory, theorems of alternative; interior-point methods. Applications to signal processing, control, digital and analog circuit design, statistics and machine learning, communications and networking, finance, and mechanical engineering. Requirements include daily exercises, including simple coding using matlab/CVX. This course should benefit anyone who uses or will use scientific computing or optimization in engineering or related work.



PhD Students/Alumni

Dip. Ingegneria dell'Informazione e Scienze Matematiche - Via Roma, 56 53100 SIENA - Italy