Structured low-rank approximation (SLRA) is a mathematical framework that seeks to approximate a given data matrix by another matrix of lower rank while preserving intrinsic structural properties.
Low-rank approximation and dimensionality reduction techniques form the backbone of modern computational methods by enabling the efficient representation of large and high‐dimensional datasets. These ...
This is a preview. Log in through your library . Abstract Gaussian process models have been widely used in spatial statistics but face tremendous computational challenges for very large data sets. The ...
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