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Found 3 papers, 1 papers with code
Asymptotic Gaussian Fluctuations of Eigenvectors in Spectral Clustering
The performance of spectral clustering relies on the fluctuations of the entries of the eigenvectors of a similarity matrix, which has been left uncharacterized until now.
A Random Matrix Approach to Low-Multilinear-Rank Tensor Approximation
This work presents a comprehensive understanding of the estimation of a planted low-rank signal from a general spiked tensor model near the computational threshold.
Two-way kernel matrix puncturing: towards resource-efficient PCA and spectral clustering
The article introduces an elementary cost and storage reduction method for spectral clustering and principal component analysis.
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