Improving Beckner's bound via Hermite functions
Paata Ivanisvili, Alexander Volberg

TL;DR
This paper improves Beckner's inequality for Gaussian measures, especially for intermediate p-values, and extends it to all real p, enhancing the understanding of functional inequalities.
Contribution
The authors provide a refined version of Beckner's inequality valid for p in [1,2], including an extension to all real p, with significant implications for Gaussian measures.
Findings
Improved inequality for p in [1,2]
Extension of inequality to all real p
Enhanced understanding of Gaussian functional inequalities
Abstract
We obtain an improvement of the Beckner's inequality valid for and the Gaussian measure. Our improvement is essential for the intermediate case , and moreover, we find the natural extension of the inequality for any real .
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.
