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Sparse matrices in data analysis

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  • Nickolay Trendafilov
  • Martin Kleinsteuber
  • Hui Zou

Abstract

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Suggested Citation

  • Nickolay Trendafilov & Martin Kleinsteuber & Hui Zou, 2014. "Sparse matrices in data analysis," Computational Statistics, Springer, vol. 29(3), pages 403-405, June.
  • Handle: RePEc:spr:compst:v:29:y:2014:i:3:p:403-405
    DOI: 10.1007/s00180-013-0468-8
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    References listed on IDEAS

    as
    1. Jianhui Chen & Jieping Ye, 2014. "Sparse trace norm regularization," Computational Statistics, Springer, vol. 29(3), pages 623-639, June.
    2. Tze Choy & Nicolai Meinshausen, 2014. "Sparse distance metric learning," Computational Statistics, Springer, vol. 29(3), pages 515-528, June.
    3. Bamdev Mishra & Gilles Meyer & Silvère Bonnabel & Rodolphe Sepulchre, 2014. "Fixed-rank matrix factorizations and Riemannian low-rank optimization," Computational Statistics, Springer, vol. 29(3), pages 591-621, June.
    4. Felix Krahmer & Gitta Kutyniok & Jakob Lemvig, 2014. "Sparse matrices in frame theory," Computational Statistics, Springer, vol. 29(3), pages 547-568, June.
    5. Clemens Hage & Martin Kleinsteuber, 2014. "Robust PCA and subspace tracking from incomplete observations using $$\ell _0$$ ℓ 0 -surrogates," Computational Statistics, Springer, vol. 29(3), pages 467-487, June.
    6. P.-A. Absil & Luca Amodei & Gilles Meyer, 2014. "Two Newton methods on the manifold of fixed-rank matrices endowed with Riemannian quotient geometries," Computational Statistics, Springer, vol. 29(3), pages 569-590, June.
    7. Nickolay Trendafilov, 2014. "From simple structure to sparse components: a review," Computational Statistics, Springer, vol. 29(3), pages 431-454, June.
    8. Max G’Sell & Shai Shen-Orr & Robert Tibshirani, 2014. "Sensitivity analysis for inference with partially identifiable covariance matrices," Computational Statistics, Springer, vol. 29(3), pages 529-546, June.
    9. Peter Bühlmann & Jacopo Mandozzi, 2014. "High-dimensional variable screening and bias in subsequent inference, with an empirical comparison," Computational Statistics, Springer, vol. 29(3), pages 407-430, June.
    10. Yixin Fang & Yang Feng & Ming Yuan, 2014. "Regularized principal components of heritability," Computational Statistics, Springer, vol. 29(3), pages 455-465, June.
    11. Charles Bouveyron & Camille Brunet-Saumard, 2014. "Discriminative variable selection for clustering with the sparse Fisher-EM algorithm," Computational Statistics, Springer, vol. 29(3), pages 489-513, June.
    Full references (including those not matched with items on IDEAS)

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