Statistical learning theory 2020 — различия между версиями

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<-- 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:
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<!-- 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.-->
 
Sanjeev Kulkarni and Gilbert Harman: An Elementary Introduction to Statistical Learning Theory, 2012.-->
  
<-- Afterward, we hope to cover chapters 1-8 from the book:
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<!-- 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/ .
 
Foundations of machine learning, Mehryar Mohri, Afshin Rostamizadeh, and Ameet Talwalker, 2012. These books can be downloaded from http://gen.lib.rus.ec/ .
  

Версия 18:24, 11 сентября 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



Office hours

Person Monday Tuesday Wednesday Thursday Friday
Bruno Bauwens Room 620