Article ID Journal Published Year Pages File Type
5773818 Journal of Complexity 2017 36 Pages PDF
Abstract
We present an approach to defining Hilbert spaces of functions depending on infinitely many variables or parameters, with emphasis on a weighted tensor product construction based on stable space splittings. The construction has been used in an exemplary way for guiding dimension- and scale-adaptive algorithms in application areas such as statistical learning theory, reduced order modeling, and information-based complexity. We prove results on compact embeddings, norm equivalences, and the estimation of ϵ-dimensions. A new condition for the equivalence of weighted ANOVA and anchored norms is also given.
Related Topics
Physical Sciences and Engineering Mathematics Analysis
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