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Showing 1 to 1 of 1 for “"Noncovex"”.

  1. Low-rank estimation and embedding learning: theory and applications

    In many real-world applications of data mining, datasets can be represented using matrices, where rows of the matrix correspond to objects (or data instances) and columns to features (or attributes). Often the datasets are in high-dimensional feature space. For example, in the vector space model of …

    uiuc Repository record for Low-rank estimation and embedding learning: theory and applications (opens in a new tab)