Markov Chains — различия между версиями

Версия 10:45, 19 ноября 2022

Lecturers and Seminarists

About the course

This page contains materials for Markov Chains course in 2022/2023 year, mandatory one for 1st year Master students of the MML 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) :

• 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 = 0.3*O_HW + 0.3*O_Mid-term + 0.4*O_Exam + 0.1*O_Bonus

with the usual (arithmetical) rounding rule.

Table with grades

Lectures and Seminars

• Link to course materials in overleaf

Homeworks

Exam

Midterm

Midterm will take place on Saturday, 07.11.2020, at 11:10. You are allowed to use your lectures and seminar notes, or any other notes or books, but NOT the laptops, mobile phones and other devices. Midterm will take 1.5 hours and it will contain 6 problems. Solving any 5 of them will give you the maximal grade.

• List of topics

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