Statistical learning theory: различия между версиями

Версия от 15:53, 13 сентября 2017

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
19 sept	Sauer's lemma, agnostic PAC-learning, structural risk minimization
26 sept	Computational learning theory
3 okt	Boosting: the adaBoost algorithm
10 okt	Boosting: several other algorithms
17 okt	Online learning algorithms

	Person	Monday	Tuesday	Wednesday	Thursday	Friday
1	Bruno Bauwens		15:05–18:00			15:05–18:00	Room 620
2	Quentin Paris

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 |-
 | 12 sept || PAC-learning and VC-dimension: proof of fundamental theorem  ||  || [https://www.dropbox.com/s/wczt02f8linttzu/2seminar.pdf?dl=0 Problem list 2]
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+| 19 sept || Sauer's lemma, agnostic PAC-learning, structural risk minimization  ||  ||
+|-
+| 26 sept ||  Computational learning theory ||  ||
+|-
+| 3 okt ||  Boosting: the adaBoost algorithm  ||  ||
+|-
+| 10 okt ||  Boosting: several other algorithms ||  ||
+|-
+| 17 okt ||  Online learning algorithms ||  ||
 |-
 |}