Coordinator: Prof. Antonio Vicino
Home |  Engineering Library |  DIISM |  Santa Chiara  | Login Privacy e Cookie policy

Info

Structure



Algorithms For Constrained Optimization

 

Prof.
Veronica Piccialli
Università di Roma Tor Vergata
Course Type
Group 1
Calendar
May 22-26 2017
Room
Program
Abstract:

1. Mathematical Programming models: introduction and first definitions
    Convex Programming (no local non global minima)
    Optimality conditions for unconstrained optimization and constrained optimization.
Special cases: convex feasible set, linear constraints, box constraints. Karush-Kuhn-Tucker conditions
    Unconstrained Optimization Algorithms: exact line search, Armijo line search. Gradient method.

2. Algorithms for Constrained Optimization Problems with convex feasible set
        Frank wolfe method
        Projected gradient method

3. Algorithms for Constrained Optimization with general constraints
        Sequential penalty method
        Augmented Lagrangian
        Exact penalty functions
        Exact Augmented Lagrangian

4. Quadratic Programming
        Wolfe duality theory
        An application: training of a  Support Vector Machine (SVM)
        Hints on decomposition methods for SVM





 

Courses

PhD Students/Alumni


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