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" Statistical learning with sparsity : "
Trevor Hastie, Stanford University, USA, Rob Tibshirani, Stanford University, USA, Martin Wainwright, University of California, Berkeley, USA
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BL
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| Record Number
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668574
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dltt
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| Main Entry
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Hastie, Trevor
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| Title & Author
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Statistical learning with sparsity : : the lasso and generalizations /\ Trevor Hastie, Stanford University, USA, Rob Tibshirani, Stanford University, USA, Martin Wainwright, University of California, Berkeley, USA
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| Series Statement
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Chapman & Hall/CRC monographs on statistics & applied probability ;; 143
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| Page. NO
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xv, 351 pages :: illustrations (some color) ;; 25 cm
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| ISBN
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9781498712163 (hardback : acid-free paper)
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: 1498712169 (hardback : acid-free paper)
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| Notes
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"A Chapman & Hall book."
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| Bibliographies/Indexes
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Includes bibliographical references and indexes
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| Contents
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Introduction -- The lasso for linear models -- Generalized linear models -- Generalizations of the lasso penalty -- Optimization methods -- Statistical inference -- Matrix decompositions, approximations, and completion -- Sparse multivariate methods -- Graphs and model selection -- Signal approximation and compressed sensing -- Theoretical results for the lasso
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| Subject
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Mathematical statistics
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Least squares
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Linear models (Statistics)
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Proof theory
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| Dewey Classification
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519.5
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| LC Classification
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QA275.H38 2015
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| Added Entry
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Tibshirani, Robert
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Wainwright, Martin, (Martin J.)
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