Statistics 311/Electrical Engineering 377: Information Theory and Statistics

Course textbook

The main textbook for the course is a set of lecture notes that Professor Duchi is developing, with the aim of turning it into a book in the near future. As a consequence, there will be mistakes in the book, mistakes in the exercises, and frequent typos. We would love it if you gave feedback (positive or negative) about things you find, and filling them out on the following Google Form will be the best way to report these. Any and all feedback is welcome!

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

Required text

• Lecture notes I am preparing for the course. These will change throughout the course, as I am rewriting them and trying to make them reflect the actual content of the course, so be sure to reload them frequently.

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.