3 papers
math.DS2026
Functional dynamic mode decomposition: Learning infinite-dimensional systems from data
Stefan Klus, Eirini Ioannou
Dynamic mode decomposition (DMD) is a data-driven method that computes the best linear approximation of the underlying dynamical system and decomposes the dynamics into a superposi…
math.DS2025
Data-driven approximation of transfer operators for mean-field stochastic differential equations
Eirini Ioannou, Stefan Klus, Gonçalo dos Reis
Mean-field stochastic differential equations, also called McKean--Vlasov equations, are the limiting equations of interacting particle systems with fully symmetric interaction pote…
stat.ML2023
Robust empirical risk minimization via Newton's method
Eirini Ioannou, Muni Sreenivas Pydi, Po-Ling Loh
A new variant of Newton's method for empirical risk minimization is studied, where at each iteration of the optimization algorithm, the gradient and Hessian of the objective functi…