Course: MCS 591, Advanced Topics in Combinatorial Theory: The Probabilistic Method
Call no: 30028
Time: MWF 11:00-11:50pm
Place: 305 Taft Hall

Professor: Dhruv Mubayi
Office: 620 SEO
E-mail: mubayi@uic.edu
Course Web Page: http://www.math.uic.edu/~mubayi/591/Spring2013/ProbMethodSpring13.html
Office Hours: TBA

Grading Policies:
You grade will be based on occasional homework assignments, class presentations, and discussions.

Disability Policy: Students with disabilities who require accommodations for access and participation in this course must be registered with the Office of Disability Services (ODS). Please contact ODS a 312/413/-2183 (voice) or 312/413-0123 (TTY).

Prerequisite: An undergraduate course in combinatorics or probability and the mathematical maturity of a graduate student.

Course Description: The probabilistic method is a powerful tool for tackling many problems in mathematics, statistics and computer science. The basic idea of the method is as follows: in order to prove that a structure with certain desired properties exists, once defines an appropriate probability space of structures and then shows that the desired properties hold in this space with positive probability. Introduced by Erdos in the 1940s to solve a basic problem in Ramsey theory, it has since proven useful in many different areas of mathematics (e.g. geometry, number theory, combinatorics) and more recently in computer science and statistics as well. The course should therefore be interesting and useful for students in a variety of fields.

This course will be a thorough introduction to the probabilistic method. While we will focus on applications in combinatorics, problems in different areas will often be explored.

A sampling of topics: Ramsey numbers, random graphs, Local Lemma, second moment method, correlation inequalities (the four function theorem and the FKG inequality), martingales, circuit complexity, discrepancy, geometric problems, derandomization.

Text: The Probabilistic Method by Alon and Spencer (third edition)

Optional Texts: Random Graphs by Bollobas (second edition), Random Graphs by Janson, Luczak, Rucinski

HW 1 Due Friday Feb 1
HW 2 Due Friday Feb 8
HW 3 Due Wednesday Feb 20
HW 4 Due Friday March 1
HW 5 Due Friday March 15
HW 6 Due Monday April 8 (note date change)
HW 7 Due Friday April 26