MC 2023
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[убрать]Lecturers and Seminarists
Lecturer | Samsonov Sergey | [svsamsonov@hse.ru] | T902 |
Seminarist | Artur Goldman | [...] | T926 |
About the course
This page contains materials for Markov Chains course in 2023/2024 year, mandatory one for 1st year Master students of the MML program (HSE and Skoltech).
Link to telegram chat: https://t.me/+9bDEStkmdi0xMWVi
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 = 0.35*OHW + 0.3*OMid-term + 0.35*OExam
with the usual (arithmetical) rounding rule.
[... Table with grades]
Lectures
- Lecture №1, 09.11
- [... Lecture №2, 18.11]
- Lecture №3, 25.11
Seminars
https://disk.yandex.ru/d/cXeyH_vL3fEb_g
Homeworks
Exam
TBD
Midterm
TBD
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://elearning.unimib.it/pluginfile.php/583708/mod_resource/content/1/1-conditional-law.pdf - Probability kernels and (regular) conditional probabilities, to the third lecture.