RL 2023 — различия между версиями

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*[https://www.overleaf.com/read/kbzmvxdzbrxq '''Lectures and seminars notes''']
 
*[https://www.overleaf.com/read/kbzmvxdzbrxq '''Lectures and seminars notes''']
 
*[https://colab.research.google.com/drive/10qBq7Ot_1ZpnTeD11P5AnE8jFVj0OLXl?usp=sharing '''Notebook for the first seminar''']
 
*[https://colab.research.google.com/drive/10qBq7Ot_1ZpnTeD11P5AnE8jFVj0OLXl?usp=sharing '''Notebook for the first seminar''']
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== Homeworks ==
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*[https://disk.yandex.ru/i/C8hwvvS5us09sA '''HW 1''']
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== Recommended literature ==
 
== Recommended literature ==

Версия 15:10, 24 ноября 2023

Lecturers and Seminarists

Lecturer Alexey Naumov [anaumov@hse.ru] T924
Seminarist Ilya Levin [tg: @levensons] T926

About the course

This page contains materials for Mathematical Foundations of Reinforcement learning course in 2023 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 = 0.6*OHW + 0.4*OProject

with the usual (arithmetical) rounding rule.

Course materials

Homeworks


Recommended literature

Homeworks

Projects