Statistical learning theory 2020
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.
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.