Hyperbolic Cross Approximation
Dinh D\~ung, Vladimir N. Temlyakov, Tino Ullrich

TL;DR
This survey reviews hyperbolic cross approximation, a multivariate technique effective in high dimensions, highlighting its theoretical foundations, practical challenges, and recent research directions to stimulate further study.
Contribution
It provides a comprehensive overview of classical and recent developments in hyperbolic cross approximation, emphasizing open problems and connections to other mathematical fields.
Findings
Hyperbolic cross approximation is effective for moderate to high dimensions.
Many fundamental problems in the area remain unsolved.
Recent connections to probability, discrepancy, and numerical integration are highlighted.
Abstract
Hyperbolic cross approximation is a special type of multivariate approximation. Recently, driven by applications in engineering, biology, medicine and other areas of science new challenging problems have appeared. The common feature of these problems is high dimensions. We present here a survey on classical methods developed in multivariate approximation theory, which are known to work very well for moderate dimensions and which have potential for applications in really high dimensions. The theory of hyperbolic cross approximation and related theory of functions with mixed smoothness are under detailed study for more than 50 years. It is now well understood that this theory is important both for theoretical study and for practical applications. It is also understood that both theoretical analysis and construction of practical algorithms are very difficult problems. This explains why…
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Taxonomy
TopicsMathematical Approximation and Integration · Advanced Numerical Analysis Techniques · Image and Signal Denoising Methods
