Differences

This shows you the differences between two versions of the page.

Link to this comparison view

Both sides previous revision Previous revision
Next revision
Previous revision
teaching:ft1920:vl:convex [2019/12/02 11:41]
ipa [Lecture Notes]
teaching:ft1920:vl:convex [2019/12/12 14:56] (current)
ipa Add logistic loss visualization
Line 44: Line 44:
 We recommend programming the exercises with Python and numpy. We recommend programming the exercises with Python and numpy.
 A basic understanding of Python and numpy should be sufficient for most exercises. A basic understanding of Python and numpy should be sufficient for most exercises.
 +
 +==== Using Mathematica ====
 +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.
 +In the notebook you can paste the code from the code files below.
 +Execute the code with Shift+Enter.
 +
  
  
Line 49: Line 56:
 You need to log in to access the lecture notes. You need to log in to access the lecture notes.
  
-{{ :​teaching:​ft1920:​vl:​convex:​files:​toc.pdf |Table of Contents (Dec 2)}} \\+{{ :​teaching:​ft1920:​vl:​convex:​files:​toc.pdf |Table of Contents (Dec 9)}} \\
 {{ :​teaching:​ft1920:​vl:​convex:​files:​introduction.pdf |Introduction (update: Oct 18)}} \\ {{ :​teaching:​ft1920:​vl:​convex:​files:​introduction.pdf |Introduction (update: Oct 18)}} \\
 {{ :​teaching:​ft1920:​vl:​convex:​files:​literature.pdf |Literature}} \\ {{ :​teaching:​ft1920:​vl:​convex:​files:​literature.pdf |Literature}} \\
Line 57: Line 64:
 {{ :​teaching:​ft1920:​vl:​convex:​files:​nonexpansiveoperators.pdf |Nonexpansive Operators (update: Nov 25)}} \\ {{ :​teaching:​ft1920:​vl:​convex:​files:​nonexpansiveoperators.pdf |Nonexpansive Operators (update: Nov 25)}} \\
 {{ :​teaching:​ft1920:​vl:​convex:​files:​coalgorithms-1.pdf |Convex Optimisation Algorithms 1}} \\ {{ :​teaching:​ft1920:​vl:​convex:​files:​coalgorithms-1.pdf |Convex Optimisation Algorithms 1}} \\
-{{ :​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}}
 ===== Exercise Sheets ===== ===== Exercise Sheets =====
 You need to log in to access the exercise sheets. You need to log in to access the exercise sheets.
Line 68: Line 76:
   - {{teaching:​ft1920:​vl:​convex:​files:​uebungsblatt6.pdf | Exercise Sheet 6}}   - {{teaching:​ft1920:​vl:​convex:​files:​uebungsblatt6.pdf | Exercise Sheet 6}}
   - {{teaching:​ft1920:​vl:​convex:​files:​uebungsblatt7.pdf | Exercise Sheet 7}}   - {{teaching:​ft1920:​vl:​convex:​files:​uebungsblatt7.pdf | Exercise Sheet 7}}
 +  - {{teaching:​ft1920:​vl:​convex:​files:​uebungsblatt8.pdf | Exercise Sheet 8}}
 +      - {{teaching:​ft1920:​vl:​convex:​files:​8_moreauenvelope.pdf | Mathematica code for visualizing the Moreau Envelope}}
 +      - {{teaching:​ft1920:​vl:​convex:​files:​8_sigmoid.pdf | Mathematica code for visualizing the Sigmoid function}}
 +      - {{teaching:​ft1920:​vl:​convex:​files:​8_logisticloss.pdf | Mathematica code for visualizing the logistic loss classifier}}
 +  - {{teaching:​ft1920:​vl:​convex:​files:​uebungsblatt9.pdf | Exercise Sheet 9}}
 +      - {{teaching:​ft1920:​vl:​convex:​files:​data_exercise_sheet_9.zip | Data}}