High-dimensional Probability and Statistics (2025): различия между версиями
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* (15.01.24) Chapter 3.1, Examples 3.5 and 3.14 from [[#blm|[BLM]]] | * (15.01.24) Chapter 3.1, Examples 3.5 and 3.14 from [[#blm|[BLM]]] | ||
* (22.01.24) Chapters 3.6-3.7 from [[#blm|[BLM]]] | * (22.01.24) Chapters 3.6-3.7 from [[#blm|[BLM]]]. For the Sobolev spaces, weak derivatives and the approximation argument, see Chapters 5.2-5.3 [[#EvansPDE | [EvansPDE]]]. See also Chapters 2.1-2.3 of [[#Ziemer | [Ziemer]]]. | ||
== Grading == | |||
The final grade is obtained as follows: | |||
0.2 HW HDP + 0.3 Midterm HDP + 0.2 HW HDS + 0.3 Exam HDS, | |||
where HW stands for home assignment, HDP stands for High-Dimensional Probability, HDS stands for High-Dimensional Statistics. | |||
= References = | = References = | ||
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<span id="paris">[Paris]</span> [https://disk.yandex.ru/i/CeIEx0MW2hpbrw Quentin Paris. Statistical Learning Theory. Lecture Notes] | <span id="paris">[Paris]</span> [https://disk.yandex.ru/i/CeIEx0MW2hpbrw Quentin Paris. Statistical Learning Theory. Lecture Notes] | ||
<span id="EvansPDE">[EvansPDE]</span> [https://disk.yandex.ru/i/cCHL2bbbr0V-7Q Lawrence Evans. Partial Differential Equations] | |||
<span id="Ziemer">[Ziemer]</span> [https://disk.yandex.ru/i/1aMzdRyaMZixCQ William Ziemer. Weakly Differentiable Equations] | |||
Версия от 17:20, 22 января 2025
Classes
Wednesdays 13:00–16:00, in room G110.
Teachers: Fedor Noskov, Quentin Paris
Teaching Assistant: Fedor Noskov
Lecture/Seminar content
Probability
- (15.01.24) Chapter 3.1, Examples 3.5 and 3.14 from [BLM]
- (22.01.24) Chapters 3.6-3.7 from [BLM]. For the Sobolev spaces, weak derivatives and the approximation argument, see Chapters 5.2-5.3 [EvansPDE]. See also Chapters 2.1-2.3 of [Ziemer].
Grading
The final grade is obtained as follows:
0.2 HW HDP + 0.3 Midterm HDP + 0.2 HW HDS + 0.3 Exam HDS,
where HW stands for home assignment, HDP stands for High-Dimensional Probability, HDS stands for High-Dimensional Statistics.
References
links are available via hse accounts
[van Handel] Ramon van Handel. Probability in High Dimensions, Lecture Notes
[Vershynin] R. Vershynin. High-Dimensional Probability
[Wainwright] M.J. Wainwright. High-Dimensional Statistics
[BLM] Boucheron et al. Concentration inequalities
[Rigollet] Philippe Rigollet and Jan-Christian H¨utter. High-Dimensional Statistics. Lecture Notes
[Paris] Quentin Paris. Statistical Learning Theory. Lecture Notes