Statistical learning theory 2020

General Information

Lectures: Saturday 9h30 - 10h50, zoom https://zoom.us/j/96210489901

Teachers: Bruno Bauwens and Vladimir Podolskii

Seminar for group 1: Saturday 11h10 - 12h30, Bruno Bauwens and Vladimir Podolskii zoom https://zoom.us/j/94186131884,

Seminar for group 2: Tuesday ??, Nikita Lukyanenko

Course materials

Date	Summary	Lecture notes	Problem list	Solutions
12 Sept	Introduction and sample complexity in the realizable setting	lecture1.pdf	Problem list 1
19 Sept	VC-dimension and sample complexity
26 Sept	Risk bounds and the fundamental theorem of statistical learning theory
03 Nov	Rademacher complexity and margin assumption

<-- A gentle introduction to the materials of the first 3 lectures and an overview of probability theory, can be found in chapters 1-6 and 11-12 of the following book: Sanjeev Kulkarni and Gilbert Harman: An Elementary Introduction to Statistical Learning Theory, 2012.-->

<-- Afterward, we hope to cover chapters 1-8 from the book: Foundations of machine learning, Mehryar Mohri, Afshin Rostamizadeh, and Ameet Talwalker, 2012. These books can be downloaded from http://gen.lib.rus.ec/ .

(We will study a new boosting algorithm, based on the paper: ) -->

Office hours

Person	Monday	Tuesday	Wednesday	Thursday	Friday
Bruno Bauwens						Room 620