Universal sampling discretization of integral norms and sparse sampling recovery

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• Feng Dai (University of Alberta)
• Monday 15 July 2024, 09:30-10:10
• Seminar Room 1, Newton Institute.

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DREW01 - Multivariate approximation, discretization, and sampling recovery

In this talk, I will report some advancements in sampling discretization and recovery.   My primary focus will be on my joint work with  E.  Kosov,   A. Prymak, A. Shadrin,  V. Temlyakov,  S. Tikhonov in this area.  The central topic of discussion will be the challenge of discretizing  $L_p$ norm in a high-dimensional space. The goal is to establish two-sided estimates of the $L_p$ norm defined with respect to a  general probability measure, using a finite sum of function values.    The uniform discretization approach applies universally to all functions in the space,  ensuring that the points are independent of any specific functions within the space.  

This talk is part of the Isaac Newton Institute Seminar Series series.

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