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Statistical learning with sparsity : the lasso and generalizations / Trevor Hastie (Stanford University, USA), Robert Tibshirani (Stanford University, USA), Martin Wainwright (University of California, Berkeley USA)

By: Contributor(s): Resource type: Ressourcentyp: BuchBookLanguage: English Series: Chapman & Hall Book | Monographs on statistics and applied probability ; 143Publisher: Boca Raton ; London ; New York : CRC Press, 2020Edition: First issued in paperbackDescription: xv, 351 Seiten : Illustrationen, DiagrammeISBN:
  • 9780367738334
  • 9781498712163
Subject(s): DDC classification:
  • 519.5
MSC: MSC: *68-02 | 62-02 | 62H12 | 62J05 | 62J07 | 68T05RVK: RVK: SK 850 | CM 4000LOC classification:
  • QA188 QA275
Summary: Front Cover; Contents; Preface; Chapter 1: Introduction; Chapter 2: The Lasso for Linear Models; Chapter 3: Generalized Linear Models; Chapter 4: Generalizations of the Lasso Penalty; Chapter 5: Optimization Methods; Chapter 6: Statistical Inference; Chapter 7: Matrix Decompositions, Approximations, and Completion; Chapter 8: Sparse Multivariate Methods; Chapter 9: Graphs and Model Selection; Chapter 10: Signal Approximation and Compressed Sensing; Chapter 11: Theoretical Results for the Lasso; Bibliography; Back CoverSummary: Discover New Methods for Dealing with High-Dimensional DataA sparse statistical model has only a small number of nonzero parameters or weights; therefore, it is much easier to estimate and interpret than a dense model. Statistical Learning with Sparsity: The Lasso and Generalizations presents methods that exploit sparsity to help recover the underlying signal in a set of data.Top experts in this rapidly evolving field, the authors describe the lasso for linear regression and a simple coordinate descent algorithm for its computation. They discuss the application of ℓ1 penalties to generalized lPPN: PPN: 1774331888
Holdings
Item type Home library Shelving location Call number Status Barcode
Freihandbestand ausleihbar Fachbibliothek Mathematik Bibliothek / frei aufgestellt Stoch. / Has Available 36609554090
Total holds: 0
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