Statistical learning theory 2021 — различия между версиями

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| || Part 1. Online learning || || ||
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| 7 Sept
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|| Introduction, the online mistake bound model, weighted majority and perceptron algorithms
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|| the standard optimal algorithm and prediction with expert advice
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|| [https://www.dropbox.com/s/kicoo9xf356eam5/01lect.pdf?dl=0 lecture1.pdf]  
 
|| [https://www.dropbox.com/s/kicoo9xf356eam5/01lect.pdf?dl=0 lecture1.pdf]  

Версия 11:15, 2 сентября 2021

General Information

Grading

Teachers: Bruno Bauwens and Nikita Lukianenko

Lectures: Tuesdays 9h30 - 10h50, zoom

Seminars: Tuesday 11h10 - 12h30

Practical information on telegram group


Course materials

Date Summary Lecture notes Problem list Solutions
Part 1. Online learning 7 Sept Introduction, the online mistake bound model, weighted majority and perceptron algorithms
the standard optimal algorithm and prediction with expert advice


The lectures in October and November are based on the book: Foundations of machine learning 2nd ed, Mehryar Mohri, Afshin Rostamizadeh, and Ameet Talwalker, 2018. This book can be downloaded from http://gen.lib.rus.ec/ .

For online learning, we also study a few topics from lecture notes by Н. К. Животовский

Office hours

Person Monday Tuesday Wednesday Thursday Friday
Bruno Bauwens, Zoom (email in advance) 14h-18h 16h15-20h Room S834 Pokrovkaya 11

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