RL 2023 — различия между версиями

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(не показано 5 промежуточных версии этого же участника)
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|| Lecturer || [https://www.hse.ru/staff/anaumov Alexey Naumov] || [anaumov@hse.ru] || T924
 
|| Lecturer || [https://www.hse.ru/staff/anaumov Alexey Naumov] || [anaumov@hse.ru] || T924
 
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|-  
|| Seminarist || [https://www.hse.ru/org/persons/219484540 Sergey Samsonov] || [svsamsonov@hse.ru] || T926
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|| Seminarist || Ilya Levin || [tg: @levensons] || T926
 
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|}
 
|}
  
 
== About the course ==
 
== About the course ==
This page contains materials for Mathematical Foundations of Reinforcement learning course in 2022/2023 year, optional one for 2nd year Master students of the Math of Machine Learning program (HSE and Skoltech).
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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 ==  
 
== Grading ==  
 
The final grade consists of 2 components (each is non-negative real number from 0 to 10, without any intermediate rounding) :
 
The final grade consists of 2 components (each is non-negative real number from 0 to 10, without any intermediate rounding) :
 
* O<sub>HW</sub> for the hometasks
 
* O<sub>HW</sub> for the hometasks
* O<sub>Project</sub> for the course project
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* O<sub>Exam</sub> for the exam
 
The formula for the final grade is  
 
The formula for the final grade is  
* O<sub>Final</sub> = 0.6*O<sub>HW</sub> + 0.4*O<sub>Project</sub>
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* O<sub>Final</sub> = 0.6*O<sub>HW</sub> + 0.4*O<sub>Exam</sub>
 
with the usual (arithmetical) rounding rule.
 
with the usual (arithmetical) rounding rule.
 
[https://docs.google.com/spreadsheets/d/1MPWVIkgxyotHU-P5cE7Gik4C6RTWxTnAVK8Btl7Fw3Y/edit?usp=sharing '''Table with grades''']
 
  
 
== Course materials ==
 
== Course materials ==
 
*[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 ==

Текущая версия на 19:19, 25 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
  • OExam for the exam

The formula for the final grade is

  • OFinal = 0.6*OHW + 0.4*OExam

with the usual (arithmetical) rounding rule.

Course materials

Homeworks


Recommended literature

Homeworks

Projects