Please note also the lectures in the
Math Machine Learning seminar organized by Guido Montúfar
Winter term 2021/2022
October 24 - 29, 2021
Geometry & Learning from Data (Online) (21w5239)
Organisers: Pablo Suárez Serrato, Minh Ha Quang, Rongjie Lai, Guido Montúfar
In this workshop we will bring together experts from academia, government stakeholders, applied researchers from industry, as well as graduate students and early career scientist to interact and develop novel solutions that apply abstract tools from high dimensional geometry to contribute to the solution of these problems.
Initiators |
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Aim | Data, in its many forms and across various disciplines, is becoming an essential source for research in the 21st century. In fact, data driven knowledge extraction nowadays constitutes one of the core paradigms for scientific discovery. Therefore, the development of efficient techniques for the integration of large data sets is more necessary than ever. Mathematics offers efficient methodologies from its various well-developed subfields for achieving this goal. Recognising the broad scientific expertise at the Max Planck Institute for Mathematics in the Sciences within the scope of data science, our initiative aims at bundling the corresponding efforts and activities in order to consolidate and advance research on Mathematics of Data. | |
Participating Groups |
![]() ![]() Geometry and Complex Systems - Jürgen Jost ![]() ![]() Pattern formation, energy landscapes, and scaling laws - Felix Otto Structure of Evolution - Matteo Smerlak ![]() Nonlinear Algebra - Bernd Sturmfels Tensors and Optimization - André Uschmajew | |
Links |
Participating group members of the Mathematics of Data Initiative are involved in various activities related to Data science,
at the MPI MiS and also at other institutions. Here is a list of links to corresponding involvements: COVID-19 Data Analysis The Mathematics Behind the Corona News Coverage ![]() ![]() ![]() ![]() ![]() ![]() ![]() |