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Feature selection in weakly coherent matrices
A problem of paramount importance in both pure (Restricted Invertibility problem) and applied mathematics (Feature extraction) is the one of selecting a submatrix of a given matrix, such that this submatrix has its smallest singular value above a specified level.
Average performance analysis of the stochastic gradient method for online PCA
This paper studies the complexity of the stochastic gradient algorithm for PCA when the data are observed in a streaming setting.
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