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University of Cambridge > Talks.cam > Isaac Newton Institute Seminar Series > Universal sampling discretization of integral norms and sparse sampling recovery
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If you have a question about this talk, please contact nobody. 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. This talk is included in these lists:
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