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teaching:ft1920:vl:convex [2020/01/17 17:10]
ipa Information about the exam
teaching:ft1920:vl:convex [2020/01/29 22:50]
ipa typos
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 ==== Place & Time ==== ==== Place & Time ====
    * **Lecture**:​ Tuesday and Friday from 11-13 in seminar room 6 in the Mathematikon (INF 205)    * **Lecture**:​ Tuesday and Friday from 11-13 in seminar room 6 in the Mathematikon (INF 205)
-   * **Exercise class**: Thursday 9-11 in seminar room 7 in the Mathematikon (INF 205), the first exercise class will be on 24th of October.+   * **Exercise class**: Thursday 9-11 in seminar room 7 in the Mathematikon (INF 205), the first exercise class will be on the 24th of October.
  
 ==== Language ==== ==== Language ====
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 ==== Target Audience ==== ==== Target Audience ====
-Students of mathematics and scientific computing that are interested ​ numerical optimization,​ with a focus on applications to data analysis and machine learning. ​+Students of mathematics and scientific computing that are interested ​in numerical optimization,​ with a focus on applications to data analysis and machine learning. ​
  
 ==== Prerequisites ==== ==== Prerequisites ====
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 ==== Using Mathematica ==== ==== Using Mathematica ====
 Go to the [[https://​www.wolfram.com/​programming-lab/​|Wolfram Programming Lab]] and click on the orange button. Go to the [[https://​www.wolfram.com/​programming-lab/​|Wolfram Programming Lab]] and click on the orange button.
-This brings you to a tutorial notebook. With the file menu in the light grey bar you can create an empty notebook. +This brings you to a tutorial notebook. With the file menu in the light grey baryou can create an empty notebook. 
-In the notebook you can paste the code from the code files below.+In the notebookyou can paste the code from the code files below.
 Execute the code with Shift+Enter. Execute the code with Shift+Enter.
  
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 {{ :​teaching:​ft1920:​vl:​convex:​files:​coalgorithms-2.pdf |Convex Optimisation Algorithms 2}} \\ {{ :​teaching:​ft1920:​vl:​convex:​files:​coalgorithms-2.pdf |Convex Optimisation Algorithms 2}} \\
 {{ :​teaching:​ft1920:​vl:​convex:​files:​conjugationduality.pdf |Conjugation,​ Duality}} \\ {{ :​teaching:​ft1920:​vl:​convex:​files:​conjugationduality.pdf |Conjugation,​ Duality}} \\
-{{ :​teaching:​ft1920:​vl:​convex:​files:​nonconvex.pdf |Nonconvex Optimization (update: Jan 17)}}+{{ :​teaching:​ft1920:​vl:​convex:​files:​nonconvex.pdf |Nonconvex Optimization (update: Jan 21)}}