Statistical learning theory 2020 — различия между версиями
Bbauwens (обсуждение | вклад) |
Bbauwens (обсуждение | вклад) |
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|| [https://www.dropbox.com/s/kicoo9xf356eam5/01lect.pdf?dl=0 Problem list 1] || <!--[https://www.dropbox.com/s/cixli4sghy0w01q/01solution.pdf?dl=0 Solutions 1]--> | || [https://www.dropbox.com/s/kicoo9xf356eam5/01lect.pdf?dl=0 Problem list 1] || <!--[https://www.dropbox.com/s/cixli4sghy0w01q/01solution.pdf?dl=0 Solutions 1]--> | ||
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− | | 19 Sept || VC-dimension and sample complexity || | + | | 19 Sept || VC-dimension and sample complexity || || || |
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− | | 26 Sept || Risk bounds and the fundamental theorem of statistical learning theory || | + | | 26 Sept || Risk bounds and the fundamental theorem of statistical learning theory || || || |
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− | | 03 Nov || Rademacher complexity and margin assumption || | + | | 03 Nov || Rademacher complexity and margin assumption || || || |
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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 |
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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 |