401-3054-14L  Probabilistic Methods in Combinatorics

SemesterAutumn Semester 2018
LecturersB. Sudakov
Periodicitynon-recurring course
Language of instructionEnglish



Courses

NumberTitleHoursLecturers
401-3054-14 VProbabilistic Methods in Combinatorics2 hrs
Thu10-12HG D 7.2 »
B. Sudakov
401-3054-14 UProbabilistic Methods in Combinatorics1 hrs
Mon15-16HG E 5 »
B. Sudakov

Catalogue data

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.

Performance assessment

Performance assessment information (valid until the course unit is held again)
Performance assessment as a semester course
ECTS credits6 credits
ExaminersB. Sudakov
Typesession examination
Language of examinationEnglish
RepetitionThe performance assessment is only offered in the session after the course unit. Repetition only possible after re-enrolling.
Mode of examinationwritten 180 minutes
Additional information on mode of examinationBe aware that no exam repetition is offered until after the course itself will be taught again in a future semester.
Written aidsIt is an open books exam.
This information can be updated until the beginning of the semester; information on the examination timetable is binding.

Learning materials

 
Main linkWebsite of the course (Moodle)
Only public learning materials are listed.

Groups

No information on groups available.

Restrictions

There are no additional restrictions for the registration.

Offered in

ProgrammeSectionType
Data Science MasterCore ElectivesWInformation
Doctoral Dep. of Information Technology and Electrical EngineeringDoctoral and Post-Doctoral CoursesWInformation
Computer Science MasterFocus Elective Courses Theoretical Computer ScienceWInformation
Computer Science MasterFocus Elective Courses General StudiesWInformation
Mathematics BachelorSelection: Mathematical Optimization, Discrete MathematicsWInformation
Mathematics MasterSelection: Mathematical Optimization, Discrete MathematicsWInformation