Where and when?

time: Thursday 2:10-4pm (w. 5mn pause at 3pm),
office hours: A. Chaintreau (Wednesday 2-3:30pm, CEPSR 610), Zeinab Abbassi (Tuesday 4:30-6pm).
room: Mudd 327

Who is teaching?

Augustin Chaintreau (instructor), Zeinab Abbassi (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:
  • a mid-term exam which deals with the “Fundamentals” materials (30%)
  • class participation (scribing , presentation in the second half) (30%)
  • a final project (research case study or topic review) (40%)

For organizational purpose, the division between presentations and projects will depend on the enrollment. It will be finalized an announce on the third course of the lectures.
Scribing should be made according to the following LaTeX template:
If you are not familiar with LaTeX, I recommend to start anyway and use the following Short Manual of LaTeX

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.