The Mathematics of Machine Learning

Co-founded by PRIN: Gradient flows, Optimal Transport and Metric Measure Structures, AFORS, CRCNSERC: Artificial Intelligence at the Interface of Chemistry and Mathematics

23 January 2023 - 27 January 2023

Invited Speakers

[table view]

Konstantin Riedl

Technical University of Munich
Talk: Evading Nonconvexity with Consensus-Based Optimization in the Mean-Field Limit

Alessandro Rudi

Institut national de recherche en sciences et technologies du numérique (INRIA)
Talk: Kernel Sums of Squares for Non-Convex Optimization with Certificates
Talk: Kernel Sums of Squares for Non-Convex Optimization with Certificates
Talk: Kernel Sums of Squares for Non-Convex Optimization with Certificates
Talk: Kernel Sums of Squares for Non-Convex Optimization with Certificates

Alessandro Scagliotti

Technical University of Munich and MCML
Talk: Normalizing Flows as Ensemble Optimal Control problems

Anna Shalova

Eindhoven Institute of Technology
Talk: Regularization properties of dropout

Ilaria Trombini

Università di Parma
Talk: Analysis of hyperparameters in the class of 1st order stochastic optimization methods

Yvonni Tsaknaki

Scuola Normale Superiore
Talk: Online Prediction of Order Flow with Bayesian Change-Point Detection Methods

Filippo Vicentini

Ecole polytechnique fédérale de Lausanne
Talk: Machine Learning for Quantum Physics
Talk: Machine Learning for Quantum Physics
Talk: Machine Learning for Quantum Physics
Talk: Machine Learning for Quantum Physics
Talk: Machine Learning for Quantum Physics
Talk: Machine Learning for Quantum Physics

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