Efficient methods in optimization
The lecture takes place on Tuesdays from 15:30 to 18:30 in room H101 (except on December 13: room H102).
Lecture 1: Introduction: modeling / formalization, problem classes, examples
Matlab implementations: uniform approximation, resource allocation, maximum flow
Lectures 2,3: Simple problems and methods, basic mathematics (convexity, affine spaces, separation, duality, faces, cones)
Matlab implementations: solution of LPs with the ellipsoid method
Lecture 4: Convexity
Lecture 5: Proximal and bundle methods
Lecture 6: Splitting methods
Lecture 7-8: Linear programming, slides
Lecture 8-9: Conic programming
Addendum: Applications of SDP
Lecture 10: Interior-point methods
Addendum: Robust conic programs
Lecture 11: Semi-definite relaxations, matlab programs Max Cut standard relaxation
Lecture 12: Polynomial optimization
There will be a 2h written exam presumably in January. The last lecture will be dedicated to training for the exam.
Some examples of problems and some other examples.