Statistics 311/Electrical Engineering 377: Information Theory and Statistics

Course textbook

The main textbook for the course is Professor Duchi's Information Theory, Learning, and Statistics, to be published by Cambridge University Press, who have generously agreed to allow us to keep pre-publication copy of the book online.

A few other texts will be part of the course as well.

Recommended texts

The following tests are not mandatory for the course, but they will give additional perspective on the material for the course.

• High Dimensional Probability, by Roman Vershynin, Cambridge University Press.

• Introduction to the non-asymptotic analysis of random matrices, by Roman Vershynin, 2012.

• High-Dimensional Statistics: A Non-Asymptotic Viewpoint, by Martin Wainwright, Cambridge University Press, 2019.

• Introduction to Nonparametric Estimation, by Alexandre Tsybakov, 2009.

• Elements of Information Theory, Second Edition, by Cover and Thomas, 2006. Wiley.

• Concentration Inequalities A Nonasymptotic Theory of Independence, by Stephane Boucheron, Gabor Lugosi, and Pascal Massart, 2013. Oxford University Press.