Lecture Notes: The lecture notes have last been updated on the 27th of November and now cover lectures 1-9.
Exams: The exams are oral exams. We offer times for oral exams on the 4th, 6th and 8th of February. After enrolling for the exam in BASIS, please contact Christiane Andrade to schedule the time of your exam.
Note: If you attend the lecture and have not done so yet, please send me a short email to this email address. Thank you!
The content of this lecture is the theoretical analysis of approximation algorithms for cluster analysis, in particular covering the following areas:
|Tuesday, 10:15-11:45||INF / Room 2.078||October 09th||Schmidt|
|October 09|| 1 Introduction
2 The happy world of k-center
2.2 A simple and elegant 2-approximation
|October 16|| 2.3 A matching lower bound
2.4 Incremental and hierarchical clustering
|October 23|| 2.4 continued: Proof
2.5 Another elegant 2-approximation
|October 30||2.6 A streaming algorithm for k-center|
|November 6||–cancelled due to illness–|
|November 13|| 2.7 The k-center problem with outliers
2.8 Fair k-center
|November 20|| 2.8 Fair k-center (ctd)
3 The exciting world of k-means
3.2 Lloyd's algorithm
|November 27|| 3.3 The k-means++ algorithm
3.3.1 D2-sampling as a bicriteria approximation
|December 4|| 3.3.2 A glimpse on the analysis of k-means++
3.4 Dimensionality reduction
|December 11||3.4.1 The Johnson-Lindenstrauss Lemma|
|December 18||3.4.2 The Singular Value Decomposition|
The lecture notes cover the content of the lecture and are updated after each lecture.