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- W2000214323 abstract "We present a few practical algorithms for sorting vectors into low-rank clusters. These algorithms rely on a subdivision scheme applied to the space of projections from d-dimensions to 1-dimension. This subdivision scheme can be thought of as a higher-dimensional generalization of quicksort. Given the ability to quickly sort vectors into low-rank clusters, one can efficiently search a matrix for low-rank sub-blocks of large diameter. The ability to detect large-diameter low-rank sub-blocks has many applications, ranging from data-analysis to matrix-compression." @default.
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- W2000214323 date "2011-06-01" @default.
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- W2000214323 title "Efficient methods for grouping vectors into low-rank clusters" @default.
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- W2000214323 doi "https://doi.org/10.1016/j.jcp.2011.03.048" @default.
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