Statistical learning theory — различия между версиями
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Bbauwens (обсуждение | вклад) м (scedule) |
Bbauwens (обсуждение | вклад) м |
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| + | For a gentle introduction to the materials I refer to the book: | ||
| + | Sanjeev Kulkarni and Gilbert Harman: An Elementary Introduction to Statistical Learning Theory, 2012. | ||
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== Office hours == | == Office hours == | ||
Версия 19:03, 13 сентября 2017
General Information
Course materials
| Date | Summary | Lecture notes | Problem list |
|---|---|---|---|
| 5 sept | PAC-learning and VC-dimension: definitions | 1st and 2nd lecture Updated on 13th of Sept. | Problem list 1 |
| 12 sept | PAC-learning and VC-dimension: proof of fundamental theorem | Problem list 2
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| 19 sept | Sauer's lemma, agnostic PAC-learning, structural risk minimization | ||
| 26 sept | Computational learning theory |
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| 3 okt | Boosting: the adaBoost algorithm | ||
| 10 okt | Boosting: several other algorithms | ||
| 17 okt | Online learning algorithms |
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For a gentle introduction to the materials I refer to the book: Sanjeev Kulkarni and Gilbert Harman: An Elementary Introduction to Statistical Learning Theory, 2012.
Office hours
| Person | Monday | Tuesday | Wednesday | Thursday | Friday | ||
|---|---|---|---|---|---|---|---|
| |
Bruno Bauwens | 15:05–18:00 | 15:05–18:00 | Room 620 | |||
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Quentin Paris |
