Stochastic analysis 2021 2022 — различия между версиями
Материал из Wiki - Факультет компьютерных наук
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*[https://www.dropbox.com/s/b8f1nyqnge6chw2/HW_1_stochan_2021.pdf?dl=0'''Homework №1, deadline: 05.10.2021, 23:59'''] [https://www.dropbox.com/s/3oeztervc7d4nf1/HW_1_stochan_2021_hints.pdf?dl=0 '''Hints'''] | *[https://www.dropbox.com/s/b8f1nyqnge6chw2/HW_1_stochan_2021.pdf?dl=0'''Homework №1, deadline: 05.10.2021, 23:59'''] [https://www.dropbox.com/s/3oeztervc7d4nf1/HW_1_stochan_2021_hints.pdf?dl=0 '''Hints'''] | ||
*[https://www.dropbox.com/s/ivasebriv46picb/HW_2_stochan_2021.pdf?dl=0'''Homework №2, deadline: 04.11.2021, 23:59'''] | *[https://www.dropbox.com/s/ivasebriv46picb/HW_2_stochan_2021.pdf?dl=0'''Homework №2, deadline: 04.11.2021, 23:59'''] | ||
+ | [https://www.dropbox.com/s/voye6c0daa42bv0/HW_2_stochan_2021_hints.pdf?dl=0 '''Hints'''] | ||
== Exam == | == Exam == |
Версия 19:59, 2 ноября 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
Seminars
Homeworks
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