Stochastic analysis 2021 2022 — различия между версиями
Материал из Wiki - Факультет компьютерных наук
Строка 24: | Строка 24: | ||
== Lectures and Seminars == | == Lectures and Seminars == | ||
− | *[https://www.dropbox.com/s/ | + | *[https://www.dropbox.com/s/xvf1x6v2frm3k9c/Seminar_11_09_stochan.pdf?dl=0 '''Lecture 11.09'''] |
− | + | ||
− | + | == Lectures and Seminars == | |
− | + | *[https://www.dropbox.com/s/xvf1x6v2frm3k9c/Seminar_11_09_stochan.pdf?dl=0 '''Seminar 11.09'''] | |
− | + | ||
− | + | ||
− | + | ||
− | + | ||
− | + | ||
− | + | ||
− | + | ||
− | + | ||
− | + | ||
− | *[https://www.dropbox.com/s/ | + | |
− | + | ||
− | + | ||
− | + | ||
− | + | ||
==Homeworks == | ==Homeworks == |
Версия 09:57, 18 сентября 2021
Содержание
Lecturers and Seminarists
Lecturer | Naumov Alexey | [anaumov@hse.ru] | T924 |
Seminarist | Samsonov Sergey | [svsamsonov@hse.ru] | T926 |
About the course
This page contains materials for Stochastic Analysis course in 2021/2022 year, mandatory one for 1st year Master students of the Statistical Learning Theory program (HSE and Skoltech).
Grading
The final grade consists of 3 components (each is non-negative real number from 0 to 10, without any intermediate rounding) :
- OHW for the hometasks
- OMid-term for the midterm exam
- OExam for the final exam
The formula for the final grade is
- OFinal = 0.3*OHW + 0.3*OMid-term + 0.4*OExam + 0.1*OBonus HW
with the usual (arithmetical) rounding rule.
Lectures and Seminars
Lectures and Seminars
Homeworks
- [Homework №1, deadline: 02.10.2020, 23:59]
Exam
Midterm
Recommended literature (1st term)
- http://www.statslab.cam.ac.uk/~james/Markov/ - Cambridge lecture notes on discrete-time Markov Chains
- https://link.springer.com/book/10.1007%2F978-3-319-97704-1 - book by E. Moulines et al, you are mostly interested in chapters 1,2,7 and 9 (book is accessible for download through HSE network)
- https://link.springer.com/book/10.1007%2F978-3-319-62226-2 - Stochastic Calculus by P. Baldi, good overview of conditional probabilities and expectations (part 4, also accessible through HSE network)
- https://link.springer.com/book/10.1007%2F978-1-4419-9634-3 - Probability for Statistics and Machine Learning by A. Dasgupta, chapter 19 (MCMC), also accessible through HSE network