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These lecture slides were written by
Stephen Boyd and
Lieven
Vandenberghe.
Introduction
Convex sets
Convex functions
Convex optimization problems
Duality
Approximation and fitting
Statistical estimation
Geometric problems
Numerical linear algebra background
Unconstrained minimization
Equality constrained minimization
Interior-point methods
Conclusions
Additional lecture notes:
Convex optimization examples
Stochastic programming
Filter design and equalization
Disciplined convex programming and CVX
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