MC 2023 — различия между версиями

Версия 12:54, 1 декабря 2023

Lecturers and Seminarists

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) :

• O_HW for the hometasks
• O_Mid-term for the midterm exam
• O_Exam for the final exam

The formula for the final grade is

• O_Final = 0.35*O_HW + 0.3*O_Mid-term + 0.35*O_Exam

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

To submit homework, join Google classroom — invite code y6dk72i

• Homework 1: Deadline 16.12.2023, 23:59

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.