047w: Approximations, Graphs, Networks, and Data Mining


Alexander Aptekarev, Keldysh Institute of Applied Mathematics
Valery Kalyagin, HSE University
Vladimir Lysov, Keldysh Institute of Applied Mathematics
Panos Pardalos, HSE University


07 October 2024 - 11 October 2024


The workshop is devoted to the development of mathematical aspects of data mining methods related with approximation and network (graph based) models. Graph and network models are our days ubiquitous in different fields of science and became more and more popular in approximations, data mining and machine learning. However, it is recognized that there is a lack of mathematical foundations for many approaches and methods of data analytics. Different aspects of network models in approximations, data mining and machine learning will be discussed. The topics of the workshop are rational approximations defined by multi-indices on an integer lattice, multi-level interpolations, reproducing kernels and operator theory on graphs. In addition, it is planned to discuss optimization of computational graph for deep learning, robustness of network models algorithms in machine learning and data mining, network models under uncertainty, multi-level network models and others.