Mathematics of Data
Seminar

Monday, Jan 28th, 2019, 11:00
Nils Bertschinger (Frankfurt Institute for Advanced Studies - FIAS, Germany)
A geometric structure underlying stock correlations
MPI MIS Leipzig, room E1 05 (Leibniz-Saal)

Thursday, Feb 14th, 2019, 11:00
Felix Krahmer (Technische Universität München)
to be announced
MPI MIS Leipzig, room E1 05 (Leibniz-Saal)

Thursday, Mar 7th, 2019, 11:00
Stefania Petra (Universität Heidelberg)
Compressed Sensing - From Theory To Practice
MPI MIS Leipzig, room E1 05 (Leibniz-Saal)

Wednesday, Apr 10th, 2019, 11:00
Gabriel Peyré (CNRS and Ecole Normale Supérieure, Paris, France)
Computational Optimal Transport for Data Sciences
MPI MIS Leipzig, room E1 05 (Leibniz-Saal)

Tuesday, May 28th, 2019, 11:15
Nicolas Garcia Trillos (Department of Statistics, University of Wisconsin-Madison, USA)
Large sample asymptotics of spectra of graph Laplacians and semilinear elliptic PDEs on random geometric graphs
MPI MIS Leipzig, room E1 05 (Leibniz-Saal)

Workshops

Spring 2019
Deep Learning Theory
(Kick-Off-Meeting of ERC Starting Grant Project)
Organiser: Guido Montúfar
MPI MIS Leipzig, room E1 05 (Leibniz-Saal)

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

April 01 - 05, 2019
Low-rank Optimization and Applications
Organiser: André Uschmajew
MPI MIS Leipzig, room E1 05 (Leibniz-Saal)

July 01 - 05, 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)

 
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

 


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