Reinforcement learning 2021 2022 — различия между версиями
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(Новая страница: «== Lecturers and Seminarists == {| class="wikitable" style="text-align:center" |- || Lecturer || [https://www.hse.ru/staff/anaumov Naumov Alexey ] || [anaumov@hs…») |
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== Seminars == | == Seminars == | ||
| − | *[https://www.dropbox.com/s/ | + | *[https://www.dropbox.com/s/wc951vseud1q1p2/Seminar_09_11_RL.pdf?dl=0 '''Seminar 09.11'''], [https://www.dropbox.com/s/2h83vbjgew1inen/Seminar_1_RL.mp4?dl=0 '''Seminar 09.11, Video'''], [https://www.dropbox.com/s/bxa8h9vjrnegsql/Bandit_intro_strategies_09_11_2021.ipynb?dl=0 '''Seminar 09.11, Notebook'''] |
==Homeworks == | ==Homeworks == | ||
Версия 23:12, 9 ноября 2021
Содержание
Lecturers and Seminarists
| Lecturer | Naumov Alexey | [anaumov@hse.ru] | T924 |
| Lecturer | Denis Belomestny | [dbelomestny@hse.ru] | T924 |
| Seminarist | Samsonov Sergey | [svsamsonov@hse.ru] | T926 |
| Seminarist | Maxim Kaledin | [mkaledin@hse.ru] | T926 |
About the course
This page contains materials for Mathematical Foundations of Reinforcement learning course in 2021/2022 year, optional one for 2nd year Master students of the Math of Machine Learning program (HSE and Skoltech).
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
- OProject for the course project
The formula for the final grade is
- OFinal = 0.5*OHW + 0.5*OProject
with the usual (arithmetical) rounding rule.
Lectures
Seminars
Homeworks
Projects
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
