Non-smooth and Non-convex Optimization

Thursday, December 10, 2015 - 11:00am - 12:00pm
Lind 305
Kazufumi Ito (North Carolina State University)
A general class of non-smooth and non-convex optimization
problems is discussed. Such problems arise in imaging analysis, control
and inverse problems and calculus of variation and much more.
Our analysis focuses on the infinite dimensional case (PDE-constaint
problem and mass transport problem and so on). The Lagrange multiplier theory is developed. Based on the theory we
develop the semi-smooth Newton method in the form of
Primal-Dual Active set method. Examples are presented to demonstrate
the theory and our analysis.
MSC Code: