
Real Algebraic Geometry, Optimization, and Machine Learning
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Description
The primary objective of this conference is to forge a new, synergistic connection between three pivotal fields: Real Algebraic Geometry, Optimization, and Machine Learning. While the links between the first two are well-established, the event focuses on creating a reciprocal, three-way dialogue to solve fundamental challenges in machine learning using powerful algebraic and optimization tools.
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Meet the speakers
F
Francis Bach
Theme:Centre Inria de Paris
D
Didier Henrion
Theme:CNRS, Université de Toulouse
S
Salma Kuhlmann
Theme:University of Konstanz
V
Victor Vinnikov
Theme:Ben Gurion University
J
James Eldred Pascoe
Theme:Washington University in St. Louis
M
Matteo Rizzi
Theme:Universität zu Köln, Forschungszentrum Jülich
A
Alessandro Rudi
Theme:Bocconi University
T
Thorsten Theobald
Theme:Goethe-Universität, Frankfurt am Main
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