August 12 - 14, 2020
MPI für Mathematik in den Naturwissenschaften Leipzig
Multidimensional sequential data appears both in time series analysis, representing a process evolving in time, and in shape analysis, representating the boundary of an object. Extracting geometric features of, and detecting symmetries in, such data is useful in their mathematical analysis and in improving the efficiency of machine learning algorithms. In recent years, both the iterated-integral signature and the moving frame method have been successfully used in this endeavor. They both provide geometrically relevant representations of sequential data, and have been used in applications ranging from mathematical nance to computer vision.
The aim of this workshop is to showcase the recent applications of these mathematical tools in data science. Introductory talks on the iterated-integrals signature and the moving frame method will provide a common language for the research presentations on current applications. The recent connection of the two communities with commutative algebra and computational algebraic tools, make the MPI for Mathematics in the Sciences, Leipzig, an attractive place to hold the meeting.
Confirmed speakers are:
University of Greifswald
MPI for Mathematics in the Sciences
Max von Renesse
Administrative ContactSaskia Gutzschebauch
MPI für Mathematik in den Naturwissenschaften
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