Summer Graduate School: Discrete Probability, Physics and Algorithms (Montréal, Canada)
Probability theory, statistics as well as mathematical physics have increasingly been used in computer science. The goal of this school is to provide a unique opportunity for graduate students and young researchers to developed multi-disciplinary skills in a rapidly evolving area of mathematics. The school will have two tutorials, two mini courses, and several two-part lectures
on: spin glasses, constraint satisfiability, randomized algorithms, Monte-Carlo Markov chains and high-dimensional statistics,
sparse and random graphs, computational complexity, estimation and approximation algorithms.
To apply to the school the students need to submit a: CV and letter of support.
The deadline to submit an application is March 15, 2019 and should be submitted through: