CUR matrix approximation is a technique used in data analysis, particularly for dimensionality reduction and low-rank approximation of large matrices. The primary goal of CUR approximation is to represent a given matrix \( A \) as the product of three smaller, more interpretable matrices: \( C \), \( U \), and \( R \).
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