Where and when?

time: Tuesday and Thursday 4:10-5:25pm
room: Mudd 1127
office hours (immediately after class, to encourage you to come):
A. Chaintreau (Thursday 5:30-7pm, CEPSR 6LW5), Avner May (Tuesday 5:30-7pm, CEPSR 6LW5).

Who is teaching?

Augustin Chaintreau (instructor), Avner May (TA).

Prerequisite?

The course requires no other knowledge that simple discrete probability, linear algebra and elementary graph theory. If you would like a refresh before taking the course, you may consider review the following notions which will be introduced.
  • Homogeneous Markov Chain: Chap.1-3 in P. Bremaud, Markov chains: Gibbs fields, Monte Carlo simulation, and queues (2010) Springer.
  • Graph Theory: Chap.1 in R. Diestel, Graph Theory (2010), Springer.
  • Linear Algebra: Matrix, eigenvalues, eigenvectors.

Grading scheme:

The evaluation will be based on:
  • 6 problem sets + class participation (to lecture or wiki)
  • a mid-term exam
  • a final exam
Exact percentage will be decided and announced on the third week (to accomodate for different attendance)

Reading, Textbook:

There is no requisite reading before the course.

Unfortunately the topic covered in this course is not described in a textbook at the graduate level.

The book Networks, Crowds, and Markets: Reasoning About a Highly Connected World, by D. Easley and J. Kleinberg may be used as a very good introduction to this course (and other topics in the domain). Relevant parts are I and IV-VI.
You can find more references in the "Additional resources" section