David Steurer: Catalogue data in Autumn Semester 2018

Name Prof. Dr. David Steurer
FieldTheoretical Computer Science
Address
Professur Theoretische Informatik
ETH Zürich, CAB H 37.1
Universitätstrasse 6
8092 Zürich
SWITZERLAND
E-maildavid.steurer@inf.ethz.ch
URLhttps://www.dsteurer.org
DepartmentComputer Science
RelationshipAssistant Professor (Tenure Track)

NumberTitleECTSHoursLecturers
252-0026-00LAlgorithms and Data Structures Information 7 credits3V + 2U + 1AM. Püschel, D. Steurer
AbstractThis course is about fundamental algorithm design paradigms, classic algorithmic problems, and data structures. The connection between algorithms and data structures is explained for geometric and graph problems. For this purpose, fundamental graph theoretic concepts are introduced.
ObjectiveAn understanding of the design and analysis of fundamental algorithms and data structures.
ContentEs werden grundlegende Algorithmen und Datenstrukturen vorgestellt und analysiert. Dazu gehören auf der einen Seite Entwurfsmuster für Algorithmen, wie Induktion, divide-and-conquer, backtracking und dynamische Optimierung, ebenso wie klassische algorithmische Probleme, wie Suchen und Sortieren. Auf der anderen Seite werden Datenstrukturen für verschiedene Zwecke behandelt, darunter verkettete Listen, Hashtabellen, balancierte Suchbäume, verschiedene heaps und union-find-Strukturen. Weiterhin wird Adaptivität bei Datenstrukturen (wie etwa Splay-Bäume) und bei Algorithmen (wie etwa online-Algorithmen) beleuchtet. Das Zusammenspiel von Algorithmen und Datenstrukturen wird anhand von Geometrie- und Graphenproblemen illustriert. Hierfür werden grundlegende Konzepte der Graphentheorie eingeführt.
LiteratureTh. Ottmann, P.Widmayer: Algorithmen und Datenstrukturen, Spektrum-Verlag, 5. Auflage, Heidelberg, Berlin, Oxford, 2011
252-0209-00LAlgorithms, Probability, and Computing Information 8 credits4V + 2U + 1AE. Welzl, M. Ghaffari, A. Steger, D. Steurer, P. Widmayer
AbstractAdvanced design and analysis methods for algorithms and data structures: Random(ized) Search Trees, Point Location, Minimum Cut, Linear Programming, Randomized Algebraic Algorithms (matchings), Probabilistically Checkable Proofs (introduction).
ObjectiveStudying and understanding of fundamental advanced concepts in algorithms, data structures and complexity theory.
Lecture notesWill be handed out.
LiteratureIntroduction to Algorithms by T. H. Cormen, C. E. Leiserson, R. L. Rivest;
Randomized Algorithms by R. Motwani und P. Raghavan;
Computational Geometry - Algorithms and Applications by M. de Berg, M. van Kreveld, M. Overmars, O. Schwarzkopf.
263-4110-00LInterdisciplinary Algorithms Lab Information Restricted registration - show details
Number of participants limited to 12.

In the Master Programme max. 10 credits can be accounted by Labs on top of the Interfocus Courses. Additional Labs will be listed on the Addendum.
5 credits2PA. Steger, D. Steurer, J. Lengler
AbstractIn this course students will develop solutions for algorithmic problems posed by researchers from other fields.
ObjectiveStudents will learn that in order to tackle algorithmic problems from an interdisciplinary or applied context one needs to combine a solid understanding of algorithmic methodology with insights into the problem at hand to judge which side constraints are essential and which can be loosened.
Prerequisites / NoticeStudents will work in teams. Ideally, skills of team members complement each other.

Interested Bachelor students can apply for participation by sending an email to steger@inf.ethz.ch explaining motivation and transcripts.