Stochastic analysis 2021 2022 — различия между версиями

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(не показано 18 промежуточных версии 2 участников)
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== Lectures ==
 
== Lectures ==
 
*[https://www.dropbox.com/s/xvf1x6v2frm3k9c/Seminar_11_09_stochan.pdf?dl=0 '''Lecture 11.09''']
 
*[https://www.dropbox.com/s/xvf1x6v2frm3k9c/Seminar_11_09_stochan.pdf?dl=0 '''Lecture 11.09''']
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*[https://www.dropbox.com/s/ejpfy7b2fl1yhq9/Stochastic%20Analysis%20Poincare%20Inequality_old.pdf?dl=0 '''Lecture 27.11''']
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*[https://www.dropbox.com/s/6c9yw85h2kz2eag/Stochastic%20Analysis%20Poincare%20Inequality.pdf?dl=0 '''Lecture 11.12''']
  
 
== Seminars ==
 
== Seminars ==
*[https://www.dropbox.com/s/i5g7a1pnbsnwclm/Seminar_18_09.pdf?dl=0 '''Seminar 18.09''']
 
 
*[https://www.dropbox.com/s/xvf1x6v2frm3k9c/Seminar_11_09_stochan.pdf?dl=0 '''Seminar 11.09''']
 
*[https://www.dropbox.com/s/xvf1x6v2frm3k9c/Seminar_11_09_stochan.pdf?dl=0 '''Seminar 11.09''']
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*[https://www.dropbox.com/s/i5g7a1pnbsnwclm/Seminar_18_09.pdf?dl=0 '''Seminar 18.09''']
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*[https://www.dropbox.com/s/xctvce7ojtfcxrm/Seminar_02_10_stochan_1st_part.pdf?dl=0 '''Seminar 02.10 (first part, Gambler's ruin was not discussed here)'''], [https://www.dropbox.com/s/3asrxd56bbljkii/Martingales.pdf?dl=0 '''Seminar 02.10 (second part, Dooob's optional sampling theorem (was provided without the proof) and Doob's maximal inequality)''']
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*[https://www.dropbox.com/s/eckkmpt0sjb1dss/Seminar_09_10_martingales.pdf?dl=0 '''Seminar 09.10 (fist part, martingales)'''], [https://www.dropbox.com/s/uit5h98bvopucso/Gaussian%20Process_2022.pdf?dl=0 '''Seminar 09.10 (secoond part, Wiener process)''']
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*[https://www.dropbox.com/s/ttdenija8cf3do1/Seminar_20_11.pdf?dl=0 '''Seminar 20.11'''][https://www.dropbox.com/s/nisy81gasxcz6ru/Seminar_20_11_2021_stochastic_analysis.mp4?dl=0 '''Seminar 20.11 (video)''']
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*[https://www.dropbox.com/s/1bhlvr2h5ul2exw/Seminar_27_11.pdf?dl=0 '''Seminar 27.11'''][https://www.dropbox.com/s/d9uw7epg8429wfw/Seminar_27_11_stochatic_analysis.mp4?dl=0 '''Seminar 27.11 (video)''']
  
 
==Homeworks ==
 
==Homeworks ==
 
*[https://www.dropbox.com/s/b8f1nyqnge6chw2/HW_1_stochan_2021.pdf?dl=0'''Homework №1, deadline: 05.10.2021, 23:59'''] [https://www.dropbox.com/s/3oeztervc7d4nf1/HW_1_stochan_2021_hints.pdf?dl=0 '''Hints''']
 
*[https://www.dropbox.com/s/b8f1nyqnge6chw2/HW_1_stochan_2021.pdf?dl=0'''Homework №1, deadline: 05.10.2021, 23:59'''] [https://www.dropbox.com/s/3oeztervc7d4nf1/HW_1_stochan_2021_hints.pdf?dl=0 '''Hints''']
*[https://www.dropbox.com/s/ivasebriv46picb/HW_2_stochan_2021.pdf?dl=0'''Homework №2, deadline: 04.11.2021, 23:59''']
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*[https://www.dropbox.com/s/ivasebriv46picb/HW_2_stochan_2021.pdf?dl=0'''Homework №2, deadline: 04.11.2021, 23:59'''][https://www.dropbox.com/s/voye6c0daa42bv0/HW_2_stochan_2021_hints.pdf?dl=0 '''Hints''']
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*[https://www.dropbox.com/s/rywaredtn30gejv/HW_3_stochan_2021.pdf?dl=0'''Homework №3, deadline: 12.12.2021, 23:59''']
  
 
== Exam ==
 
== Exam ==
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*[https://www.dropbox.com/s/aev6kyohfb2a0kd/Questions_stochan_2021_Final.pdf?dl=0 '''List of questions''']
  
 
==Midterm ==
 
==Midterm ==
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Midterm will take place on Saturday, 13.11.2020, at 11:00. Midterm is open-book, all materials are allowed. Midterm will take 3 hours and it will contain 6 problems. Solving any 5 of them will give you the maximal grade.
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*[https://www.dropbox.com/s/gqeaq9vwonfex02/Questions_stochan_midterm_2021.pdf?dl=0 '''List of topics''']
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*[https://www.dropbox.com/s/1oxswu950umhtqw/consult_10_11_stochan.mp4?dl=0 '''Consultation, video'''], [https://www.dropbox.com/s/5pmn8i3yqzdkt6n/%D0%91%D0%BB%D0%BE%D0%BA%D0%BD%D0%BE%D1%82%20%D0%B1%D0%B5%D0%B7%20%D0%BD%D0%B0%D0%B7%D0%B2%D0%B0%D0%BD%D0%B8%D1%8F%20%2838%29%20%282%29.pdf?dl=0 '''Consultation, notes''']
  
 
== Recommended literature (1st term) ==
 
== Recommended literature (1st term) ==
*http://www.statslab.cam.ac.uk/~james/Markov/ - Cambridge lecture notes on discrete-time Markov Chains
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*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)
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*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)
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*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
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*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;
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*http://th.if.uj.edu.pl/~gudowska/dydaktyka/Oksendal.pdf - Stochastic Differential Equations by Bernt Oksendal, chapters 3-4-5 provide a construction of the Stochastic integral and all required information on SDE's.

Текущая версия на 23:59, 15 декабря 2021

Lecturers and Seminarists

Lecturer Naumov Alexey [anaumov@hse.ru] T924
Seminarist Samsonov Sergey [svsamsonov@hse.ru] T926

About the course

This page contains materials for Stochastic Analysis course in 2021/2022 year, mandatory one for 1st year Master students of the Statistical Learning Theory program (HSE and Skoltech).

Grading

The final grade consists of 3 components (each is non-negative real number from 0 to 10, without any intermediate rounding) :

  • OHW for the hometasks
  • OMid-term for the midterm exam
  • OExam for the final exam

The formula for the final grade is

  • OFinal = 0.3*OHW + 0.3*OMid-term + 0.4*OExam + 0.1*OBonus HW

with the usual (arithmetical) rounding rule.

Table with grades

Lectures

Seminars

Homeworks

Exam

Midterm

Midterm will take place on Saturday, 13.11.2020, at 11:00. Midterm is open-book, all materials are allowed. Midterm will take 3 hours and it will contain 6 problems. Solving any 5 of them will give you the maximal grade.

Recommended literature (1st term)