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Approximation of Ridge Functions and Sparse Additive Models

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ASCW01 - Challenges in optimal recovery and hyperbolic cross approximation

The approximation of smooth multivariate functions is known to suffer the curse of dimension. We discuss approximation of structured multivariate functions, which take the form of a ridge, their sum, or of the so-called sparse additive models. We give also results about optimality of such algorithms.

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

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