Instructor: Prof. Vadim Kaimanovich
Email: vkaimano@uOttawa.ca
Course Website: https://sites.google.com/view/markov-chains-and-random-walks/home
Registration Deadline: September 24th, 2021
Lecture Times: Mondays | 1:00 pm - 2:30 pm and Wednesdays | 11:30 am - 1:00 pm  
Course Dates: September 8th - December 8th, 2021
Mid-Semester Break: October 25th - 29th, 2021
Grading: Assignments and a written report

Course Overview

Random walks is an umbrella term for Markov chains on state spaces endowed with additional structures (e.g., on graphs or groups). This area is currently very active with numerous connections ranging from purely theoretical aspects of, say, group theory or hyperbolic geometry, to very applied topics such as data mining and machine learning. The purpose of the course is both to introduce the theory of random walks and to show how it illustrates a number of fundamental notions often neglected in applied expositions: Lebesgue (standard) probability spaces, conditional probabilities and martingales, entropy and Kullback-Leibler divergence, law of large numbers and subadditive ergodic theorem, etc.

Course Website