Dimension independent Bernstein-Markov inequalities in Gauss space
Alexandros Eskenazis, Paata Ivanisvili

TL;DR
This paper establishes a dimension-independent Bernstein-Markov inequality in Gaussian space, providing bounds on polynomial derivatives and integrals involving the Ornstein-Uhlenbeck generator, with implications for high-dimensional analysis.
Contribution
The paper introduces a novel Bernstein-Markov inequality in Gaussian space that is independent of dimension, extending classical polynomial inequalities to high-dimensional settings.
Findings
Dimension-independent bounds for polynomial derivatives in Gaussian space.
New integral inequalities involving the Ornstein-Uhlenbeck generator.
Explicit constants and growth conditions for polynomial inequalities.
Abstract
We obtain the following dimension independent Bernstein-Markov inequality in Gauss space: for each there exists a constant such that for any and all polynomials on we have where is the standard Gaussian measure on . We also show that under some mild growth assumptions on any function with we have where is the generator of the…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
