2 papers
stat.ML2026
Distributionally Faithful Imputation via Positive Semi-Definite Kernel Density Estimation
Andrea Basteri, Carlo Ciliberto, Alessandro Rudi
Missing values undermine statistical inference and machine learning pipelines, yet most imputation methods rely on heuristics or restrictive parametric assumptions that ignore the…
cs.LG2025
Non-Parametric Learning of Stochastic Differential Equations with Non-asymptotic Fast Rates of Convergence
Riccardo Bonalli, Alessandro Rudi
We propose a novel non-parametric learning paradigm for the identification of drift and diffusion coefficients of multi-dimensional non-linear stochastic differential equations, wh…