【摘 要】
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The reconstruction of multivariate functions from a limited sets of pointwise samples is an important problem in a number of applications.In this talk I wil
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The reconstruction of multivariate functions from a limited sets of pointwise samples is an important problem in a number of applications.In this talk I will present an infinite-dimensional framework for this problem based on weighted l1 minimization.This framework general,and applies to arbitrary point sets and expansion systems.I will explain why working in infinite dimensions is important,describe the critical role that weights play in the formulation,and address recovery guarantees.
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