031w: Data Analytics, Networks and Approximation

Alexander Aptekarev, Keldysh Institute of Applied Mathematics
Panos Pardalos, University of Florida & Higher School of Economics, Nizhny Novgorod
Valery Kalyagin, Higher School of Economics, Nizhny Novgorod
Vladimir Lysov, Keldysh Institute of Applied Mathematics

The school-conference is devoted to mathematical methods of data analysis related to network models. The main goal is to develop the fundamentals of network analysis and their connection with modern empirical and engineering approaches. Applications of network models in data analysis and machine learning will be considered as well. The approximation aspect, which is crucial in computer modeling, will also be covered. The main tools here are rational approximations defined by multi-indices on an integer lattice, quadrature formulas, Christoffel-Darboux kernels, operator theory on graphs. The program of the school-conference includes invited lectures and talks, as well as special sessions with talks by young researchers. 

Program

External website