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
01/24 | Introduction | David Huck Gutman
02/07 | Basic Inequalities | Adrian Hagerty
02/14 | Bounding the Variance | David Itkin
02/21 | Basic Information Inequalities | Antoine Remond-Tiedrez
02/28 | Logarithmic Sobolev Inequalities | Won Eui Hong
03/07, 03/21 | The Entropy Method | Son Van
03/28, 04/04 | Isoperimetric Inequalities | Adrian Hagerty
04/25, 05/02 | The Transport Method | David Itkin
Summaries of the key points from each talk can be found in these notes.