Mathematical Foundations of Data Science Reading Group

We are a group of graduate students from Departments of Statistics, Mathematics, Computer Sciences, Electrical and Computer Engineering at UW-Madison.

This reading group is an informal weekly meeting to discuss advanced mathematical tools, which are widely applied in data science. Every semester we choose a topic to study based on the group's interests.

Time: 4 - 5:30 pm, Tuesday

Venue: CS3310

Summer 2019

We will be discussing the lecture notes of the course A Theoretician's Toolkit by Santosh Vempala.

References -

• A Theoretician's Toolkit(Lecture notes by Santosh Vempala)
• The Modern Algorithmic Toolbox (Lecture notes by Gregory Valiant)

Spring 2019

We discussed the monograph Randomized algorithms in numerical linear algebra.

References -

• Randomized algorithms in numerical linear algebra (Survey by Ravindran Kannan and Santosh Vempala)
• Lecture Notes on Randomized Linear Algebra (by Michael W. Mahoney)
• Sketching as a Tool for Numerical Linear Algebra (by David P. Woodruff)

We also discussed a few chapters from the textbook Probability on Trees and Networks.

References -

• Probability on Trees and Networks (Textbook by Russell Lyons and Yuval Peres)
• Algebraic combinatorics of electrical networks (Lecture notes by Pavlo Pylyavskyy)

Winter 2018

We mainly discussed Modern Convex Geometry notes by Keith Ball.

References -

• An elementary introduction to Modern Convex Geometry (Monograph by Keith Ball)
• (ACG) Algorithmic Convex Geometry (Lecture Notes by Santosh Vempala), Different Version
• Geometric Functional Analysis (Lecture Notes by Roman Vershynin, Scribe by Yuting Yang)

Summer and Fall 2018

Schedule for the textbook High-Dimensional Probability by Roman Vershynin.

We also briefly discussed Statistics and Information Theory lecture notes by John Duchi.

Spring 2018

The topic of this semester is Random Matrix Theory, we'll discuss Terence Tao's notes.