Maxim Kaledin
- Lecturer:Faculty of Computer Science / Big Data and Information Retrieval School
- Junior Research Fellow, Doctoral Student:Faculty of Computer Science / International Laboratory of Stochastic Algorithms and High-Dimensional Inference
- Maxim Kaledin has been at HSE University since 2015.
Research Projects
PDF document describing possible research directions: https://www.overleaf.com/read/wgjhsykvbwxm
Postgraduate Studies
3rd year of study
Approved topic of thesis: Uncertainty quantification in reinforcement learning
Academic Supervisor: Беломестный Денис Витальевич
Courses (2021/2022)
- Mathematical Foundations of Reinforcement learning (Master’s programme; Faculty of Computer Science; 2 year, 2 module)Eng
- Numerical Methods (Bachelor’s programme; Faculty of Computer Science; 3 year, 3, 4 module)Rus
- Stochastic Processes (Bachelor’s programme; Faculty of Computer Science; 4 year, 3 module)Rus
- Past Courses
Courses (2020/2021)
- Numerical Methods (Bachelor’s programme; Faculty of Computer Science; 4 year, 3 module)Rus
- Numerical Methods (Bachelor’s programme; Faculty of Computer Science; 3 year, 3, 4 module)Rus
Courses (2019/2020)
- Numerical Methods (Bachelor’s programme; Faculty of Computer Science; 4 year, 3 module)Rus
- Numerical Methods (Bachelor’s programme; Faculty of Computer Science; 3 year, 3, 4 module)Rus
Publications2
- Chapter Kaledin M., Moulines E., Naumov A., Tadic V., Wai H. Finite Time Analysis of Linear Two-timescale Stochastic Approximation with Markovian Noise, in: Proceedings of Machine Learning Research Vol. 125: Proceedings of Thirty Third Conference on Learning Theory. , 2020. P. 2144-2203.
- Article Беломестный Д. В., Kaledin M., Schoenmakers J. Semitractability of optimal stopping problems via a weighted stochastic mesh algorithm // Mathematical Finance. 2020. Vol. 30. No. 4. P. 1591-1616. doi
Employment history
Research
Dec 2020 - now Research Fellow, HDI Lab, Higher School of Economics, main topics: stochastic optimal control, high-dimensional probability theory.
Apr 2018 - Dec 2020 Research Intern, HDI Lab, Higher School of Economics, main topics: stochastic optimal control, high-dimensional probability theory.
Jul-Aug 2018 Research Intern, Huawei Moscow Research Center, main topics: antenna modelling, FDD systems.
Teaching
2017-now Lecturer, Numerical Methods, third-year bachelor's course (HSE, Faculty of Computer Science).
Sept-Dec 2019 Lecturer, Stochastic Calculus, OZON Masters School.
Sept-Dec 2018 Teaching Assistant, Stochastic Calculus, MS-1 course (HSE, Faculty of Computer Science, Statistical Learning Theory MS program).
Sept-Dec 2016 Teaching Assistant, Numerical Methods, third-year bachelor's course (HSE faculty of Computer Science).
Apr-Jun 2015,2016,2017 Teaching Assistant, Abstract Algebra, first-year bachelor's course (HSE Faculty of Computer Science).
First Cohort Graduates from Master’s Programme in Statistical Learning Theory
The Master's Programme in Statistical Learning Theory was launched in 2017. It is run jointly with the Skolkovo Institute of Science and Technology (Skoltech). The programme trains future scientists to effectively carry out fundamental research and work on new challenging problems in statistical learning theory, one of the most promising fields of science. Yury Kemaev and Maxim Kaledin, from the first cohort of programme graduates, sat down with HSE News Service to talk about their studies and plans for the future.
First Cohort Graduates from Master’s Programme in Statistical Learning Theory
The Master's Programme ‘Statistical Learning Theory’ was launched in 2017, and is run jointly with the Skolkovo Institute of Science and Technology(Skoltech).