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teaching:wt21:vl:co [2021/10/15 14:21]
ipa [Convex Optimization]
teaching:wt21:vl:co [2021/10/19 23:08] (current)
ipa [Registration]
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   * **Exercises:​** Stefania Petra, Matthias Zisler   * **Exercises:​** Stefania Petra, Matthias Zisler
   * **Lecture room:** 2.103 (Mathematikon)   * **Lecture room:** 2.103 (Mathematikon)
 +  * **Times:** Wed 11.15-12.45 (lecture), Thu 14.15-15.45 (tutorial)
   * **Format:**   * **Format:**
       * In-person lecture were we also explain each subtopic from a top-down viewpoint. ​       * In-person lecture were we also explain each subtopic from a top-down viewpoint. ​
       * Detailed lecture notes that you read on your own.       * Detailed lecture notes that you read on your own.
       * Exercise sheets you work on your own. Solutions will be discussed in person.       * Exercise sheets you work on your own. Solutions will be discussed in person.
-      * We will use Teams for exchanging ​lecture ​material. +      * We will use [[https://​teams.microsoft.com/​l/​team/​19%3a6KJMfXAitgm3vq72JEDFEh2zXuwm4RoIWX7yGBZrIvs1%40thread.tacv2/​conversations?​groupId=943028f7-9974-4480-9a62-3ecea8546719&​tenantId=3d057f2f-8466-43fd-8a56-5d334d13d895|Microsoft ​Teams]] for communication and distributing ​lecture ​content.
-     +
   * **Language:​** English   * **Language:​** English
   * **SWS:** 4   * **SWS:** 4
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   * **Registration:​** Please register in Teams.   * **Registration:​** Please register in Teams.
   * **Prior Knowledge:​** Required: Lineare Algebra and Analysis   * **Prior Knowledge:​** Required: Lineare Algebra and Analysis
 +
 +
 +==== Registration ====
 +
 +If you have not activated your UNI ID for Teams  please use this form
 +https://​it-service.uni-heidelberg.de/​anfrage/​teams_benutzer_freischalten\\
 +You can use this code for joining Teams: bf3fhns
  
 ==== Content ==== ==== Content ====
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   * //​Preliminaries//:​ Convex sets, convex functions, convex optimization problems (LPs, QPs, SOCPs, SDPs)   * //​Preliminaries//:​ Convex sets, convex functions, convex optimization problems (LPs, QPs, SOCPs, SDPs)
   * //Theory//: Separation theorems, duality, subdifferential calculus, existence and optimality   * //Theory//: Separation theorems, duality, subdifferential calculus, existence and optimality
-  * //​Algorithms//:​ Gradient-based methods for smooth optimization,​ proximal-point and splitting methods +  * //​Algorithms//:​ Gradient-based methods for smooth optimization,​ proximal-point and splitting methods ​for non-smooth optimization 
-  * //​Applications//:​ Convex models in mathematical imaging+  * //​Applications//:​ Convex models in mathematical imaging ​and data science
  
 ==== Literature ==== ==== Literature ====