Here is a short survival guide on how to pass this course and a few study materials, like my cheatsheet and the teach center questions with space in between if you want to print it out.

Cheatsheet beinhaltet alle 70 Fragen und die meisten proofs

Fragenkatalogausarbeitung von den neuen 78 Fragen. Alle Fragen außer die letzten 5 beantwortet.

Formelsammlung für die Prüfung inklusive Beweisen und fast alles von den Folien. Sehr detailliert, und nicht ganz alles ist am Scan erkennbar. Aber zumindest als Anhaltspunkt kanns dienen beim Zusammenschreiben.

Vercschwommen, aber lesbar.

Exam questions of OCS/NumOpt exams over the last couple of years + some more examples. Exam of 11.12.2023 is already included. Dont worry about the pages, left a little space to answer after each question ;)

Handwritten solutions for assignment 1 from 2022
Matrix Calculus with all intermediate steps
Full points

Handwritten solution for Automatic Differentiation in a simple feedforward neural network from the first assignment
Full points

Handwritten Proofs from the first assignment WS 2022
Regarding vector forms and matrices
Full points

Exam from 3.3.2023 under Prof Pock
Only Exam Questions, not answered
(Check the other document for some of the answers)

Exam for Numerical Optimization and Optimization for Computer Science.

This document is far from covering all possible questions but it should give you an overview of what questions were asked in the past.
Featuring Exams from 3.3.2023, 17.11.2022, 2.2.2022, the 24 hour Exams simple Pen and Paper Tasks and Janurary 2021 (The one with Kalman Filter and Matrix Calculus and a lot of old questions from Optimization forComputer Science (OCS))
For stationary points always also check the neighbourhood for non/strict Maximas
For Convex Opt be prepared having to also perform the other methods like CG method
Not every question is completely correct, there may be some flaws here and there so feel free to correct and upload them.
However, this document was enough for me to get a 2 on the exam so the answers here are (at least somewhat) correct. Also learn the 54 provided questions from the Teach Center and all proofs you never know what gets asked:
Be prepared that there always is at least one completely new question worth 15+ points
GLHF :)
-
Some important erros/remarks:
The question at page 43 is missing the unrestricted x4 check, same as for x2.
The L_inf Norm and the drawings of Norms and the convex constraint set should be drawn in a way s.t. the constraint set not being entirely inside the convex set
The question with Lagrange f(a,b) can be found on TUBE from WS 2021.
Also always check neighbours for strict/nonstrict at stationary point tasks

All 54 questions from the PDF in Teach Center answered, including some basic Examples for Optimality Conditions, Simplex, CG Method, etc. - No guarantee for correctness - If you find any mistake or something is unclear, feel free to join the Numerische Optimierung Discord Server: https://discord.gg/7jBM7ZD2QW
-
Study hard YOLO harder
-
Changelog:
At question 49 the L1 Ball convex set is not drawn correctly, please refer to google for how the L1 Ball looks like

An old OCS exam - questions very similar to the current questions from the pdf in teach center

Example Exam Questions for "Numerische Optimierung" (INF) (Fragenkatalog)
The 54 questions provided by the prof which should give you an idea what might get asked. Rarely these even get asked 1:1

About 95 percent of the questions are answered. Not sure if they are completely correct

Angabe der 24 Stunden Prüfung ohne Ausarbeitung

Questions of the oral exam (29.01.2020)