Statistical learning theory 2020

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General Information

Teachers: Bruno Bauwens and Vladimir Podolskii

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

Seminars
- Group 1: Saturday 11h10 - 12h30, Bruno Bauwens and Vladimir Podolskii zoom https://zoom.us/j/94186131884,
- Group 2: Tuesday 18h, Nikita Lukyanenko, see ruz.hse.ru

Practical information on telegram group

Homeworks: deadlines every 2 weeks, before the lecture.
- Sat 3 Oct: see problem lists 1 (updated) and 2
- Sat 17 Oct: see problem lists 3 and 4
- etc.

Results.

Email homeworks to Brbauwens <at> gmail.com. Start the subject line with SLT-HW. You may submit handwritten solutions.

Course materials

Date Summary Lecture notes Slides Video Problem list Solutions
12 Sept Introduction and sample complexity in the realizable setting lecture1.pdf slides1.pdf Problem list 1 Update 26.09, prob 1.7 Solutions 1
19 Sept VC-dimension and sample complexity lecture2.pdf slides2.pdf Chapt 2,3 Problem list 2 Solutions 2
26 Sept Risk bounds and the fundamental theorem of statistical learning theory lecture3.pdf slides3.pdf Problem list 3 Solutions 3
03 Oct Rademacher complexity lecture4.pdf
10 Oct AdaBoost and the margin assumption
17 Oct Support vector machines, kernels and neural networks


The lectures in October are based on 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/ .


Office hours

Person Monday Tuesday Wednesday Thursday Friday
Bruno Bauwens 14h-18h 16h15-20h Room S834 Pokrovkaya 11

It is always good to send an email in advance. Questions are welcome.