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Regular version of the site

International Laboratory of Stochastic Algorithms and High-Dimensional Inference

Low-rank diffusion matrix estimation for high-dimensional time-changed Levy processes

Belomestny D., Trabs M.

Annales de l'institut Henri Poincare (B) Probability and Statistics. 2018. Vol. 54. No. 3. P. 1583-1621.

The International Laboratory of Stochastic Algorithms and High-Dimensional Inference was created in April 2018 and is part of the Faculty of Computer Science at HSE.

Russian and international researchers work at the laboratory at the intersection of numerous mathematical disciplines, including modern statistics, optimisation, probability theory and theory of computation. Its main aim is to develop new probability and statistical approaches to current problems in the field of data analysis. 


Math of Machine Learning Contest Now Open

Until April 20, you can apply to take part in the Math of Machine Learning 2021 contest. The winners of the contest will be able to enrol into HSE University's Math of Machine Learning master's programme and  Skoltech's Data Science master's programme (Math of Machine Learning track) without entrance exams.

Eight new candidates of computer science in 2020

We are proud to announce that in 2020 eight candidates of computer science defended their theses at the Faculty. There have been six candidate defences in 2019. Prior to 2018, there were only degrees of candidate and doctor of technical or physical-mathematical sciences in Russia. Degrees in computer science have become possible due to HSE University's ability to grant its own degrees.

HSE University Becomes the First Russian University to Confer a Doctoral Degree in Computer Science

Upon successfully defending his dissertation before HSE Dissertation Council in Computer Science, Pavel Dvurechensky became the first Doctor of Computer Science in Russia. This was possible thanks to the fact that, starting in 2018, HSE University received the right to award its own academic degrees.

Conference "Foundations of Modern Statistics (Moscow edition)" on the occasion of Vladimir Spokoiny's 60th birthday, November 30, 2019

Foundations of Modern Statistics Workshop will be held at HSE University (Pokrovsky Boulevard, 11, R504) on November 30, 2019. The topics include, but not limited to: Mathematical statistics, Optimization, Econometrics, Stochastic analysis.

Structural Inference in High-Dimensional Models 2, Pushkin, August 26-30, 2019

On August 26–30, 2019, the International Laboratory of Stochastic Algorithms and High Dimensional Inference (HDI Lab) held the Second Annual Conference ‘Structural Inference in High-Dimensional Models’. The focus of the event this year was on the following topics:
– High-dimensional probability and statistics;
– Statistical and computational optimal transport;
– Markov Chain Monte-Carlo (MCMC);
– Deep-network mathematics.

Second Joint Olympiad in Statistical Learning Theory

HSE's Faculty of Computer Science and Skoltech are pleased to announce the launch of the second joint Olympiad in Statistical Learning Theory (SLT). The competition will be open to undergraduate and graduate students specializing in fields related to Applied Mathematics and Informatics. Following a pre-selection phase (application details below), the Olympiad finals will be held at Skoltech on April 6-7, 2019.

Mini-course "Advanced Statistical Methods" by HDI Lab Chief Research Fellow, Professor Vladimir Spokoiny

Vladimir Spokoiny (WIAS, Berlin; HSE, Moscow) will give a mini-course "Advanced Statistical Methods" on February 11, 14, 18, 21, 25, 28 and April 8, 11.

Eric Moulines published a monograph "Markov Chains" at Springer

Markov Chains, authors: Douc, R., Moulines, E., Priouret, P., Soulier, P.

We are hiring!

International laboratory of stochastic algorithms and high-dimensional inference (HDI Lab) invites applications for postdoctoral research positions in the field of high-dimensional probability and statistics as well as their fruitful applications. It is expected that the appointed candidates will take an active part in the project aimed at development and analysis of new efficient computational statistical algorithms for high-dimensional and challenging statistical problems like uncertainty quantification for MCMC algorithms, Bayesian inference, covariance estimation, estimation of barycenters etc. Particularly promising will be the research at the junction of the main topics of this project

Acedemic advisor of the HDI Lab, prof. Eric Moulines, gave a mini-course "Introduction to Markov chains and Markov processes"

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