Angelika Steger: Catalogue data in Autumn Semester 2023

Award: The Golden Owl
Name Prof. Dr. Angelika Steger
FieldInformatik (Theoretische Informatik)
Address
Inst. f. Theoretische Informatik
ETH Zürich, OAT Z 27
Andreasstrasse 5
8092 Zürich
SWITZERLAND
E-mailsteger@inf.ethz.ch
URLhttp://www.cadmo.ethz.ch/as/people/professor/asteger/index
DepartmentComputer Science
RelationshipFull Professor

NumberTitleECTSHoursLecturers
252-0209-00LAlgorithms, Probability, and Computing Information 8 credits4V + 2U + 1AB. Gärtner, R. Kyng, A. Steger, D. Steurer, E. Welzl
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).
Learning 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.
252-4202-00LSeminar in Theoretical Computer Science Information Restricted registration - show details 2 credits2SE. Welzl, B. Gärtner, M. Hoffmann, J. Lengler, A. Steger, D. Steurer, B. Sudakov
AbstractPresentation of recent publications in theoretical computer science, including results by diploma, masters and doctoral candidates.
Learning objectiveThe goal is to introduce students to current research, and to enable them to read, understand, and present scientific papers.
Prerequisites / NoticeThis seminar takes place as part of the joint research seminar of several theory groups. Intended participation is for students with excellent performance only. Formal restriction is: prior successful participation in a master level seminar in theoretical computer science.
263-0006-00LAlgorithms Lab Restricted registration - show details 8 credits4P + 3AA. Steger, E. Welzl
AbstractStudents learn how to solve algorithmic problems given by a textual description (understanding problem setting, finding appropriate modeling, choosing suitable algorithms, and implementing them). Knowledge of basic algorithms and data structures is assumed; more advanced material and usage of standard libraries for combinatorial algorithms are introduced in tutorials.
Learning objectiveThe objective of this course is to learn how to solve algorithmic problems given by a textual description. This includes appropriate problem modeling, choice of suitable (combinatorial) algorithms, and implementing them (using C/C++, STL, CGAL, and BGL).
LiteratureT. Cormen, C. Leiserson, R. Rivest: Introduction to Algorithms, MIT Press, 1990.
J. Hromkovic, Teubner: Theoretische Informatik, Springer, 2004 (English: Theoretical Computer Science, Springer 2003).
J. Kleinberg, É. Tardos: Algorithm Design, Addison Wesley, 2006.
H. R. Lewis, C. H. Papadimitriou: Elements of the Theory of Computation, Prentice Hall, 1998.
T. Ottmann, P. Widmayer: Algorithmen und Datenstrukturen, Spektrum, 2012.
R. Sedgewick: Algorithms in C++: Graph Algorithms, Addison-Wesley, 2001.