263-4400-00L  Advanced Graph Algorithms and Optimization

SemesterFrühjahrssemester 2020
DozierendeR. Kyng
Periodizitätjährlich wiederkehrende Veranstaltung
KommentarNumber of participants limited to 30.


263-4400-00 GAdvanced Graph Algorithms and Optimization3 Std.
Mi09:15-12:00CAB G 52 »
R. Kyng
263-4400-00 AAdvanced Graph Algorithms and Optimization1 Std.R. Kyng


KurzbeschreibungThis course will cover a number of advanced topics in optimization and graph algorithms.
LernzielThe course will take students on a deep dive into modern approaches to
graph algorithms using convex optimization techniques.

By studying convex optimization through the lens of graph algorithms,
students should develop a deeper understanding of fundamental
phenomena in optimization.

The course will cover some traditional discrete approaches to various graph
problems, especially flow problems, and then contrast these approaches
with modern, asymptotically faster methods based on combining convex
optimization with spectral and combinatorial graph theory.
InhaltStudents should leave the course understanding key
concepts in optimization such as first and second-order optimization,
convex duality, multiplicative weights and dual-based methods,
acceleration, preconditioning, and non-Euclidean optimization.

Students will also be familiarized with central techniques in the
development of graph algorithms in the past 15 years, including graph
decomposition techniques, sparsification, oblivious routing, and
spectral and combinatorial preconditioning.
Voraussetzungen / BesonderesThis course is targeted toward masters and doctoral students with an
interest in theoretical computer science.

Students should be comfortable with design and analysis of algorithms, probability, and linear algebra.

Having passed the course Algorithms, Probability, and Computing (APC) is highly recommended, but not formally required. If you are not
sure whether you're ready for this class or not, please consult the


Information zur Leistungskontrolle (gültig bis die Lerneinheit neu gelesen wird)
Leistungskontrolle als Semesterkurs
ECTS Kreditpunkte5 KP
PrüfendeR. Kyng
Formbenotete Semesterleistung
RepetitionRepetition nur nach erneuter Belegung der Lerneinheit möglich.
Zusatzinformation zum PrüfungsmodusGraded Homework 1: 15 % of grade. Homework consists entirely of exercises.

Graded Homework 2: 15 % of grade. 10 % is for exercises, 5 % is for a short written report on a paper. The lecturer will assign papers to students, possibly with some input from students. Assignments are done individually.

Oral exam: 70 % of the grade. Exam is 30 minutes, of which 15 minutes will be spent on the paper associated with the written report, and 15 minutes will be spent covering topics from the lectures.


Es werden nur die öffentlichen Lernmaterialien aufgeführt.


Keine Informationen zu Gruppen vorhanden.


PlätzeMaximal 30
WartelisteBis 01.03.2020

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