CS 594 Geometric algorithms for data analysis
Spring, 2018
Intructors:
Anastasios Sidiropoulos
Time:
Mon Wed, 4:005:15pm
Location:
TBH 180C
Office hours:
Mon 2:003:00pm, SEO 1240
Course description
Relevant textbooks

S. HarPeled, Geometric approximation algorithms. AMS, 2011.

J. Matousek, Lectures on discrete geometry. Springer, 2002.
Homework
TBA
Lectures

Jan 17, 2018. Lecture 1: Introduction. Clustering I.
Additional reading material:

Jan 22, 2018. Lecture 2: Clustering II.

Jan 24, 2018. Lecture 3: Clustering III.
Additional reading material:

Jan 29, 2018. Lecture 4: Dimensionality reduction.
Additional reading material:

Jan 31, 2018. Lecture 5: Geometric realizations of metrical data I:
Embedding into L_{∞}.
Bourgain's theorem and its extensions.
Additional reading material:

Feb 5, 2018. Lecture 6: Geometric realizations of metrical data II.

Feb 7, 2018. Lecture 7: Geometric realizations of graphs: Spectral embeddings. Spectral partitioning.
Additional reading material:

Feb 12, 2018. Lecture 8: Nearest neighbor search I.
Additional reading material:

Feb 14, 2018. Lecture 9: Nearest neighbor search II.