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	<title>MC 2023 - История изменений</title>
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	<updated>2026-06-06T12:14:44Z</updated>
	<subtitle>История изменений этой страницы в вики</subtitle>
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		<title>imported&gt;Art-gold1579: /* Homeworks */</title>
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		<updated>2024-03-09T09:38:32Z</updated>

		<summary type="html">&lt;p&gt;&lt;span class=&quot;autocomment&quot;&gt;Homeworks&lt;/span&gt;&lt;/p&gt;
&lt;p&gt;&lt;b&gt;Новая страница&lt;/b&gt;&lt;/p&gt;&lt;div&gt;== Lecturers and Seminarists ==&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;text-align:center&amp;quot;&lt;br /&gt;
|-&lt;br /&gt;
|| Lecturer || [https://www.hse.ru/org/persons/219484540 Samsonov Sergey ] || [svsamsonov@hse.ru] || T902&lt;br /&gt;
|- &lt;br /&gt;
|| Seminarist || [https://www.hse.ru/org/persons/225526439 Artur Goldman] || [...] || T926&lt;br /&gt;
|-&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
== About the course ==&lt;br /&gt;
This page contains materials for Markov Chains course in 2023/2024 year, mandatory one for 1st year Master students of the MML program (HSE and Skoltech).&lt;br /&gt;
&lt;br /&gt;
Link to telegram chat: https://t.me/+9bDEStkmdi0xMWVi&lt;br /&gt;
&lt;br /&gt;
== Grading == &lt;br /&gt;
The final grade consists of 3 components (each is non-negative real number from 0 to 10, without any intermediate rounding) :&lt;br /&gt;
* O&amp;lt;sub&amp;gt;HW&amp;lt;/sub&amp;gt; for the hometasks&lt;br /&gt;
* O&amp;lt;sub&amp;gt;Mid-term&amp;lt;/sub&amp;gt; for the midterm exam&lt;br /&gt;
* O&amp;lt;sub&amp;gt;Exam&amp;lt;/sub&amp;gt; for the final exam  &lt;br /&gt;
The formula for the final grade is &lt;br /&gt;
* O&amp;lt;sub&amp;gt;Final&amp;lt;/sub&amp;gt; = 0.35*O&amp;lt;sub&amp;gt;HW&amp;lt;/sub&amp;gt; + 0.3*O&amp;lt;sub&amp;gt;Mid-term&amp;lt;/sub&amp;gt; + 0.35*O&amp;lt;sub&amp;gt;Exam&amp;lt;/sub&amp;gt;&lt;br /&gt;
with the usual (arithmetical) rounding rule.&lt;br /&gt;
&lt;br /&gt;
[... &amp;#039;&amp;#039;&amp;#039;Table with grades&amp;#039;&amp;#039;&amp;#039;]&lt;br /&gt;
&lt;br /&gt;
== Lectures ==&lt;br /&gt;
* [https://disk.yandex.ru/i/UN0f7EuYK0G9jQ Lecture №1, 09.11]&lt;br /&gt;
* [... Lecture №2, 18.11]&lt;br /&gt;
* [https://disk.yandex.ru/i/c3wEPZ1zYaCI_g Lecture №3, 25.11]&lt;br /&gt;
* [https://disk.yandex.ru/i/CfhWKmbAOaEgEw Lecture №4, 02.12]&lt;br /&gt;
* [https://disk.yandex.ru/d/nM_XKLm4BfILhw Lecture №5-6, 16.12]&lt;br /&gt;
* [https://disk.yandex.ru/i/I8M-SoWlLHl3Ag Lecture №7, 13.01]&lt;br /&gt;
* [https://disk.yandex.ru/i/7F6gH0mFBcnn_w Lecture №8, 20.01]&lt;br /&gt;
&lt;br /&gt;
== Seminars ==&lt;br /&gt;
https://disk.yandex.ru/d/cXeyH_vL3fEb_g&lt;br /&gt;
&lt;br /&gt;
== Homeworks ==&lt;br /&gt;
To submit homework, join&lt;br /&gt;
[https://classroom.google.com/c/NjM4ODgyNjE1ODEw?cjc=y6dk72i &amp;#039;&amp;#039;&amp;#039;Google classroom&amp;#039;&amp;#039;&amp;#039;] — invite code &amp;#039;&amp;#039;&amp;#039;y6dk72i&amp;#039;&amp;#039;&amp;#039;&lt;br /&gt;
&lt;br /&gt;
Homework solution file should be readable and well-organized.&lt;br /&gt;
* [https://disk.yandex.ru/i/UH2fNs3vp6qtFA Homework 1: Deadline 13.01.2024, 23:59]&lt;br /&gt;
* [https://disk.yandex.ru/i/S2MdBKkH4_J0jA Homework 2: Deadline 03.02.2024, 23:59]&lt;br /&gt;
* [https://disk.yandex.ru/i/WVysij7PyiKD4Q Homework 3: Deadline 17.03.2024, 23:59]&lt;br /&gt;
* [https://disk.yandex.ru/i/xFgnBzy6GNy2Uw Homework 4: Deadline 23.03.2024, 23:59]&lt;br /&gt;
&lt;br /&gt;
== Exam ==&lt;br /&gt;
TBD&lt;br /&gt;
&lt;br /&gt;
==Midterm ==&lt;br /&gt;
TBD&lt;br /&gt;
&lt;br /&gt;
== Recommended literature (1st term) ==&lt;br /&gt;
*http://www.statslab.cam.ac.uk/~james/Markov/ - Cambridge lecture notes on discrete-time Markov Chains&lt;br /&gt;
*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)&lt;br /&gt;
*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)&lt;br /&gt;
*https://elearning.unimib.it/pluginfile.php/583708/mod_resource/content/1/1-conditional-law.pdf - Probability kernels and (regular) conditional probabilities, to the third lecture.&lt;br /&gt;
&lt;br /&gt;
== Useful links ==&lt;br /&gt;
Energy based models:&lt;br /&gt;
*Tutorial from seminar: https://uvadlc-notebooks.readthedocs.io/en/latest/tutorial_notebooks/tutorial8/Deep_Energy_Models.html&lt;br /&gt;
*Important work on EBM: https://openai.com/research/energy-based-models&lt;br /&gt;
*Other EBM related works of the same author: https://energy-based-model.github.io/Energy-based-Model-MIT/&lt;br /&gt;
*Another tutorial on EBM from CVPR 2021: https://energy-based-models.github.io/&lt;br /&gt;
*Another tutorial on EBM from Yann LeCun: https://www.cs.toronto.edu/~vnair/ciar/lecun1.pdf&lt;br /&gt;
*Comparisson between generative models: https://arxiv.org/pdf/2103.04922.pdf&lt;/div&gt;</summary>
		<author><name>imported&gt;Art-gold1579</name></author>
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