Statistical Signal Processing |
► Course Info |
► Video Lectures |
► Course Material |
Advanced Optimization |
► Course Info |
► Course Material |
Optimization |
► Course Info |
AI Algorithms |
This course targets competences in formulating, analyzing, and solving non-linear optimization problems. As opposed to the introductory course IKT720, here problems are not necessarily convex. The first part deals with the formulation and theoretical analysis of optimization problems. The second part is concerned with algorithms.
Linear algebra, analysis, convex optimization, MATLAB programming.
Since I could not find any reference collecting all the material that I deemed most relevant, I wrote these lecture notes, which have gradually grown over the years. These notes are intended to serve as i) material for self-study, ii) lecturing material, and iii) reference. To achieve this end, the contents are clearly structured and explicitly organized to the paragraph level.
Since this topic may be difficult to digest, the student is expected to carefully study the lecture notes before each session. A collection of quiz questions throughout the notes prompt the student to reflect on the concepts presented there, review additional material when necessary, and stimulate persistence in the student's long-term memory. The answers to the quiz questions can be submitted before the corresponding lecture to obtain extra grade points.
The lectures then build the big picture and query students to both help them understand the core concepts and to detect those parts that were not understood. They follow a guided flipped-classroom approach.