Stein’s method and functional inequalities in machine learning

The multivariate functional de Jong CLT

Autori: Christian Döbler, Mikołaj Kasprzak,Giovanni Peccati
Pubblicato in: Probability Theory and Related Fields, Numero 184, 2022, Pagina/e 367–399, ISSN 0178-8051
Editore: Springer Verlag
DOI: 10.1007/s00440-022-01114-3

Vector-valued statistics of binomial processes: Berry-Esseen bounds in the convex distance

Autori: Mikołaj Kasprzak, Giovanni Peccati
Pubblicato in: Annals of Applied Probability, 2023, ISSN 1050-5164
Editore: Institute of Mathematical Statistics

A Targeted Accuracy Diagnostic for Variational Approximations

Autori: Wang, Yu; Kasprzak, Mikołaj; Huggins, Jonathan H.
Pubblicato in: Proc. of the 26th International Conference on Artificial Intelligence and Statistics (AISTATS), Numero 25-27 April 2023, 2023
Editore: Proceedings of Machine Learning Research
DOI: 10.48550/arxiv.2302.12419

A Fourier Representation of Kernel Stein Discrepancy with Application to Goodness-of-Fit Tests for Measures on Infinite Dimensional Hilbert Spaces

Autori: George Wynne, Mikołaj Kasprzak, Andrew Duncan
Pubblicato in: 2022
Editore: ArXiv

How good is your Laplace approximation of the Bayesian posterior? Finite-sample computable error bounds for a variety of useful divergences

Autori: Mikołaj Kasprzak, Ryan Giordano, Tamara Broderick
Pubblicato in: 2022
Editore: ArXiv

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