Autumn Semester 2020 takes place in a mixed form of online and classroom teaching.
Please read the published information on the individual courses carefully.

Benjamin Sudakov: Catalogue data in Autumn Semester 2018

Name Prof. Dr. Benjamin Sudakov
FieldMathematics
Address
Professur für Mathematik
ETH Zürich, HG G 65.1
Rämistrasse 101
8092 Zürich
SWITZERLAND
Telephone+41 44 632 40 28
E-mailbenjamin.sudakov@math.ethz.ch
URLhttp://www.math.ethz.ch/~sudakovb
DepartmentMathematics
RelationshipFull Professor

NumberTitleECTSHoursLecturers
252-4202-00LSeminar in Theoretical Computer Science Information
The deadline for deregistering expires at the end of the second week of the semester. Students who are still registered after that date, but do not attend the seminar, will officially fail the seminar.
2 credits2SE. Welzl, B. Gärtner, M. Hoffmann, J. Lengler, A. Steger, B. Sudakov
AbstractPresentation of recent publications in theoretical computer science, including results by diploma, masters and doctoral candidates.
ObjectiveThe goal is to introduce students to current research, and to enable them to read, understand, and present scientific papers.
401-3054-14LProbabilistic Methods in Combinatorics Information 6 credits2V + 1UB. Sudakov
AbstractThis course provides a gentle introduction to the Probabilistic Method, with an emphasis on methodology. We will try to illustrate the main ideas by showing the application of probabilistic reasoning to various combinatorial problems.
Objective
ContentThe topics covered in the class will include (but are not limited to): linearity of expectation, the second moment method, the local lemma, correlation inequalities, martingales, large deviation inequalities, Janson and Talagrand inequalities and pseudo-randomness.
Literature- The Probabilistic Method, by N. Alon and J. H. Spencer, 3rd Edition, Wiley, 2008.
- Random Graphs, by B. Bollobás, 2nd Edition, Cambridge University Press, 2001.
- Random Graphs, by S. Janson, T. Luczak and A. Rucinski, Wiley, 2000.
- Graph Coloring and the Probabilistic Method, by M. Molloy and B. Reed, Springer, 2002.