New frontiers in high-dimensional probability and statistics 2
Interantional Laboratory of stochastic algorighms and high-dimensional inference (HDI Lab) invites you to joint winter school aimed at undergraduate/graduate students and young postdoctoral fellows from pure and applied mathematics. Participants will learn about modern trends in high-dimensional probability and statistics together with their fruitful applications. This intense two-day workshop will consist of 3 interdisciplinary mini-courses by world-class scientists and talks by the participants (mainly MS student of Statistical learning theory program and PhD students). Key topics of this school:
- Markov Chain Monte-Carlo (MCMC)
- High-dimensional principal component analysis (PCA)
- Manifold learning
- Adaptive estimation
- Optimal transport
- Machine learning
We also present MS program Statistical Learning Theory, which is a joint program of HSE and Skoltech. This program stands at the crossroads of various disciplines of modern mathematics and computer science, including statistics, optimization, learning theory, information theory, complexity theory, as well as at the intersection of science and innovation in the field of modern information technology. Leading experts at HSE and Skoltech jointly provide instruction in this unique research-driven program. Participants of the winter school will have opportunity to ask questions about the program and meet lecturers.
The winter school will be held at the National Research University Higher School of Economics, 20 Myasnitskay Str., Moscow, RUSSIA. Registration of any person willing to participate is mandatory.