Statistical learning theory 2020 — различия между версиями
Bbauwens (обсуждение | вклад) |
Bbauwens (обсуждение | вклад) |
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(не показаны 23 промежуточные версии этого же участника) | |||
Строка 10: | Строка 10: | ||
- Group 2: Tuesday 18h, Nikita Lukyanenko, see [https://ruz.hse.ru ruz.hse.ru] | - Group 2: Tuesday 18h, Nikita Lukyanenko, see [https://ruz.hse.ru ruz.hse.ru] | ||
− | + | Practical information on [https://t.me/joinchat/DZPMBRkbM5uX1l9e0pj_LQ telegram group] | |
Homeworks: deadlines every 2 weeks, before the lecture. <br> | Homeworks: deadlines every 2 weeks, before the lecture. <br> | ||
− | - | + | - Sat 3 Oct: see problem lists 1 and 2 <br> |
− | - | + | - Sat 17 Oct: see problem lists 3 and 4<br> |
− | - | + | - Sat 31 Oct: see problem list 5<br> |
+ | - Sat 14 Nov: see problem lists 6 and 7<br> | ||
+ | - Sat 28 Nov: see problem lists 8 and 9<br> | ||
+ | - Sat 12 Dec: see problem lists 10 and 11 | ||
[https://www.dropbox.com/s/z5q5ib34abybj06/scores.ods?dl=0 Results.] | [https://www.dropbox.com/s/z5q5ib34abybj06/scores.ods?dl=0 Results.] | ||
Строка 50: | Строка 53: | ||
| 03 Oct || Rademacher complexity | | 03 Oct || Rademacher complexity | ||
|| [https://www.dropbox.com/s/ggw79gau85a4mcl/04lect.pdf?dl=0 lecture4.pdf] | || [https://www.dropbox.com/s/ggw79gau85a4mcl/04lect.pdf?dl=0 lecture4.pdf] | ||
+ | || [https://www.dropbox.com/s/pd2ockzxqdfo66t/04slides.pdf?dl=0 slides4.pdf] | ||
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+ | || [https://www.dropbox.com/s/rbx6jwlusnwhkzn/04sem.pdf?dl=0 Problem list 4] <span style="color:red">Update 09.10, prob 4.3,4.6</span> | ||
+ | || [https://www.dropbox.com/s/nhxkxfjajzsgfnf/04sol.pdf?dl=0 Solutions 4] | ||
+ | |- | ||
+ | | 10 Oct || Support vector machines and risk bounds | ||
+ | || Chapt 5, Mohri et al, see below | ||
+ | || [https://www.dropbox.com/s/q2onm9o6wgceg5i/05slides.pdf?dl=0 slides5.pdf] | ||
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+ | || [https://www.dropbox.com/s/upv70of97fqpx5f/05sem.pdf?dl=0 Problem list 5] <span style="color:red">Update 12.10, added background info</span> | ||
+ | || [https://www.dropbox.com/s/jfneptto1qoug1g/05sol.pdf?dl=0 Solutions 5] | ||
+ | |- | ||
+ | | 17 Oct || Support vector machines and kernels. | ||
+ | || [https://www.dropbox.com/s/7zi67710l4zdnyv/06lect.pdf?dl=0 lecture6.pdf] | ||
+ | || [https://www.dropbox.com/s/tot9akaoonja1zp/06slides.pdf?dl=0 slides6.pdf] | ||
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+ | || [https://www.dropbox.com/s/y7w3srgsrp9d7m0/06sem.pdf?dl=0 Problem list 6] | ||
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− | | | + | | 31 Oct || Adaboost |
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+ | | 07 Nov || Online learning 1 | ||
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+ | | 14 Nov || Online learning 2 | ||
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+ | | 21 Nov || Active learning | ||
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+ | | 28 Nov || Unsupervised learning | ||
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+ | | 5 Dec || Optional: Neural networks and stochastic gradient descent | ||
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+ | | 12 Dec || Optional: Neural networks and stochastic gradient descent | ||
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Строка 73: | Строка 126: | ||
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.--> | ||
− | + | The lectures in October are based on the book: | |
− | Foundations of machine learning, Mehryar Mohri, Afshin Rostamizadeh, and Ameet Talwalker, | + | 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/ . |
− | + | In November, we follow the [http://machinelearning.ru/wiki/index.php?title=%D0%A2%D0%B5%D0%BE%D1%80%D0%B8%D1%8F_%D1%81%D1%82%D0%B0%D1%82%D0%B8%D1%81%D1%82%D0%B8%D1%87%D0%B5%D1%81%D0%BA%D0%BE%D0%B3%D0%BE_%D0%BE%D0%B1%D1%83%D1%87%D0%B5%D0%BD%D0%B8%D1%8F_(%D0%BA%D1%83%D1%80%D1%81_%D0%BB%D0%B5%D0%BA%D1%86%D0%B8%D0%B9%2C_%D0%9D._%D0%9A._%D0%96%D0%B8%D0%B2%D0%BE%D1%82%D0%BE%D0%B2%D1%81%D0%BA%D0%B8%D0%B9) lecture notes] by Н. К. Животовский | |
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== Office hours == | == Office hours == |
Версия 00:34, 17 октября 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 and 2
- Sat 17 Oct: see problem lists 3 and 4
- Sat 31 Oct: see problem list 5
- Sat 14 Nov: see problem lists 6 and 7
- Sat 28 Nov: see problem lists 8 and 9
- Sat 12 Dec: see problem lists 10 and 11
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 | slides4.pdf | Problem list 4 Update 09.10, prob 4.3,4.6 | Solutions 4 | |
10 Oct | Support vector machines and risk bounds | Chapt 5, Mohri et al, see below | slides5.pdf | Problem list 5 Update 12.10, added background info | Solutions 5 | |
17 Oct | Support vector machines and kernels. | lecture6.pdf | slides6.pdf | Problem list 6 | ||
31 Oct | Adaboost | |||||
07 Nov | Online learning 1 | |||||
14 Nov | Online learning 2 | |||||
21 Nov | Active learning | |||||
28 Nov | Unsupervised learning | |||||
5 Dec | Optional: Neural networks and stochastic gradient descent | |||||
12 Dec | Optional: Neural networks and stochastic gradient descent |
The lectures in October 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/ .
In November, we follow the lecture notes by Н. К. Животовский
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.