Laboratory for High-dimensionality and Big Data
Grant Agreement No.: 14.W03.31.0031
Project name: High-dimensional approximation, recovery and compression with applications in Big Data analysis
Name of the institution of higher learning: Lomonosov Moscow State University
Fields of scientific research: Mathematics
The goal is to develop the theoretial foundations of data siene and, in partiular, to takle fundamental mathematiсal problems in the area of high-dimensional approximation. This will lay down the theoretiсal foundations for big data proсessing, whiсh is very important in reation of big data proсessing systems, maсhine learning and artiсial intelligenсe solutions. The main foсus will be on problems with potential praсtiсal appliсations.
Name: Temlyakov Vladimir Nikolaevich
Academic degree and title: Dr. Hab.
Job Title: Carolina Distinguished Professor
Field of scientific interests: sparse, greedy approximation, learning, high-dimensional, hyperbolic cross
2003 – Award USC Education Foundation
2012 - Best Paper Award, Journal of Complexity
Scientific work of the leading scientist, his/her main scientific achievements:
At a moment Temlyakov is actively working in two rapidly developing areas of mathematics - greedy approximation and multivariate approximation. The intense study of approximation in the mixed smoothness classes began in 1960s, mostly, in the Moscow mathematical school. The last two decades have seen a great increase in research in this area. Temlyakov is published a monograph and a book on the topic. These are the only fundamental books on the topic.
V.N.Temlyakov, D.Bilyk, Rui Yu, Fibonacci sets and symmetrization in discrepancy Theory, 2012 Journal of complexity
V.N.Temlyakov, E.Liu Super greedy type algorithms 2012 Advances in Computational Mathematics
V.N.Temlyakov, K.Kazarian Hilbert spaces of vectorvalued functions generated by quadratic forms 2013 Journal of Mathematical Analysis and Applications
V.N.TemlyakovAn inequality for the entropy numbers and its application 2013 Journal of Approximation Theory
V.N.Temlyakov, G. Kerkyacharian, V. Kolchinskii, D. Picard, and A. Tsybakov Optimal exponential bounds on the accuracy of classification 2014 Constructive Approximation