This semester we will be working on ‘‘Concentration of measures: The Theoretical Foundation of Machine Learning’’.

Text: ‘‘Concentration inequalities: a nonasymptotic theory of independence’’ by Boucheron, Lugosi and Massart.

Email for the working groups is: siam-wg@lists.andrew.cmu.edu

Schedule (so far)

Name Date(s) Topic
David Huck Gutman 01/24 Introduction
Adrian Hagerty 02/07 Basic inequalities
David Itkin 02/14 Bounding the variance
Antoine Remond-Tiedrez 02/21 Basic information inequalities
Won Eui Hong 02/28 Logarithmic Sobolev inequalities
Son Van 03/07, 21 The entropy method
Adrian Hagerty 03/28, 04/04 Isoperimetric inequalities
TBD 04/18 TBD
David Itkin 04/25, 05/02 The transport method

Summaries of the key points from each talk can be found in these notes.