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 systems biology, computational geometry,
statistics, machine learning, and electrical engineering.
- استاد: مجتبی تفاق