MC 2025: различия между версиями

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Homework results:
Homework results:
* [https://docs.google.com/spreadsheets/d/161zusCoAHYV7ISXrNjaTBJrgbUVyQBC8wYMjFB_EyWc/edit?usp=sharing link ]
* [https://docs.google.com/spreadsheets/d/17GA7C4FQIEViFIKD3UGBKoqZNkuT_YiYqtvnnBY34to/edit?usp=sharing link ]


== Exam ==
== Exam ==

Текущая версия от 20:13, 26 января 2026

Lecturers and Seminarists

Lecturer Sergey Samsonov [svsamsonov@hse.ru] T904
Seminarist Marina Sheshukova [msheshukova@hse.ru] T926

About the course

This page provides materials for the Markov Chains course (2025/2026), which is mandatory for 1st-year Master’s students in the MML program (HSE and Skoltech). Please, join the Telegram Group.

Grading

The final grade consists of 2 components (each is non-negative real number from 0 to 10, without any intermediate rounding) :

  • OHW for the hometasks
  • OExam for the final exam

The formula for the final grade is

  • OFinal = 0.5*OHW + 0.5*OExam

with the usual (arithmetical) rounding rule.

Lectures and Seminars

  • [1] - Lectures and seminars from current academic year (videos)
  • [2] - Lectures from 2024-2025 academic year, slightly different topics
  • [3] - Lectures from 2023-2024 academic year, slightly different topics
  • [4] - Seminars from 2023-2024 academic year, slightly different topics
  • [5] - Lectures and seminars notes (last update: 06.12.2025)

Homeworks

To submit homework, join Google classroom — invite code w5anjhzk

Homework solution file should be readable and well-organized.

Homework results:

Exam

TBD

Recommended literature

  • Leonid B. Koralov Yakov G. Sinai - Theory of Probability and Random Processes;
  • Yuri Suhov, Mark Kelbert - Probability and Statistics by Example: Volume 2;
  • Randal Douc , Eric Moulines , Pierre Priouret , Philippe Soulier - Markov Chains.