Eigenvalue problems are a cornerstone of modern applied mathematics, arising in diverse fields from quantum mechanics to structural engineering. At their heart, these problems seek scalar values and ...
Principal component analysis (PCA) is a widely used method for dimension reduction. In high-dimensional data, the "signal" eigenvalues corresponding to weak principal components (PCs) do not ...
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