Mathematics of Data
Seminar

Tuesday, May 28th, 2019, 11:15
Nicolas Garcia Trillos (Department of Statistics, University of Wisconsin-Madison, USA)
The use of geometry to learn from data, and the learning of geometry from data.
MPI MIS Leipzig, room E1 05 (Leibniz-Saal)

Tuesday, Jul 16th, 2019, 11:00
Lamiae Azizi (The University of Sydney)
A Mathematical trip into the Data Science realm
MPI MIS Leipzig, room E1 05 (Leibniz-Saal)

Courses

Summer term 2019

Nihat Ay: Artificial Neural Networks and Machine Learning: Theoretical Foundations II
MPI MIS Leipzig, room A3 02, Thursday 11:15, starting April 18

Jürgen Jost: Information and Complexity
MPI MIS Leipzig, room A3 02, Friday 13:30, starting April 26

Mateusz Michałek, Bernd Sturmfels: Invitation to Nonlinear Algebra
MPI MIS Leipzig, room G3 10, block course, details see link

Workshops

March 11 - June 14, 2019
Geometry and Learning from Data in 3D and Beyond
Co-Organisator: Guido Montúfar
Location: IPAM at University of California

July 01 - 04, 2019
Summer School on Probabilistic and Statistical Thinking in Nonlinear Algebra
Organiser: Paul Breiding, Jesus De Loera, Despina Stasi, Sonja Petrovic
MPI MIS Leipzig, room E1 05 (Leibniz-Saal)

March 30 - April 03, 2020
Spring School of Mathematical Statistics
Organiser: Carlos Améndola, Eliana Duarte Gelvez, Orlando Marigliano
MPI MIS Leipzig, room E1 05 (Leibniz-Saal)

 
Initiators Nihat Ay, Christiane Görgen, Guido Montúfar, André Uschmajew 
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 Information Theory of Cognitive Systems
Nihat Ay

Algebraic Statistics
Christiane Görgen

Geometry and Complex Systems
Jürgen Jost

Deep Learning Theory
Guido Montúfar

Opinion dynamics and cultural Conflict in European Spaces
Eckehard Olbrich

Structure of Evolution
Matteo Smerlak

Bioinformatics (Leipzig University)
Peter F. Stadler

Nonlinear Algebra
Bernd Sturmfels

Tensors and Optimization
André Uschmajew

 


Imprint