Stochastic analysis 2020 2021 — различия между версиями
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This page contains materials for Stochastic Analysis course in 2020/2021 year, mandatory one for 1st year Master students of the Statistical Learning Theory program (HSE and Skoltech). | This page contains materials for Stochastic Analysis course in 2020/2021 year, mandatory one for 1st year Master students of the Statistical Learning Theory program (HSE and Skoltech). | ||
| − | == Grading | + | == Grading == |
The final grade consists of 3 components (each is non-negative real number from 0 to 10, without any intermediate rounding) : | The final grade consists of 3 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 | ||
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* O<sub>Final</sub> = 0.3*O<sub>HW</sub> + 0.3*O<sub>Mid-term</sub> + 0.4*O<sub>Exam</sub> | * O<sub>Final</sub> = 0.3*O<sub>HW</sub> + 0.3*O<sub>Mid-term</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'''] | ||
== Lectures and Seminars == | == Lectures and Seminars == | ||
Версия 03:41, 7 ноября 2020
Содержание
Lecturers and Seminarists
| Lecturer | Naumov Alexey | [anaumov@hse.ru] | T924 |
| Lecturer | Belomestny Denis | [dbelomestny@hse.ru] | T926 |
| Seminarist | Samsonov Sergey | [svsamsonov@hse.ru] | T926 |
About the course
This page contains materials for Stochastic Analysis course in 2020/2021 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
with the usual (arithmetical) rounding rule. Table with grades
Lectures and Seminars
- Lecture 05.09
- Lecture 12.09
- Lecture 19.09
- Seminar 19.09
- Lecture-Seminar 26.09, part 1 (Martingales)
- Lecture-Seminar 26.09, part 2 (Wiener process)
- Lecture 03.10
- Seminar 03.10
- Lecture 17.10
- Seminar 31.10
Homeworks
Midterm
Midterm will take place on Saturday, 07.11.2020, at 11:10. You are allowed to use your lectures and seminar notes, or any other notes or books, but NOT the laptops, mobile phones and other devices. Midterm will take 1.5 hours and it will contain 6 problems. Solving any 5 of them will give you the maximal grade.
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
