Singular value

Results: 1733



#Item
1Fast Randomized Singular Value Thresholding for Nuclear Norm Minimization Tae-Hyun Oh∗ KAIST thoh.kaist.ac.kr @gmail.com

Fast Randomized Singular Value Thresholding for Nuclear Norm Minimization Tae-Hyun Oh∗ KAIST thoh.kaist.ac.kr @gmail.com

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Source URL: www-infobiz.ist.osaka-u.ac.jp

Language: English - Date: 2015-04-12 20:28:56
    2Stat 991: Multivariate Analysis, Dimensionality Reduction, and Spectral Methods  Lecture: 1 The Singular Value Decomposition Instructor: Sham Kakade

    Stat 991: Multivariate Analysis, Dimensionality Reduction, and Spectral Methods Lecture: 1 The Singular Value Decomposition Instructor: Sham Kakade

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    Source URL: stat.wharton.upenn.edu

    Language: English - Date: 2010-01-22 00:50:27
      31  Exercise session 4 Internal Stability of LFT. Structured Singular Value µ . Structured Robust Stability and Performance. µ Synthesis via D − K iterations.  Reading Assignment

      1 Exercise session 4 Internal Stability of LFT. Structured Singular Value µ . Structured Robust Stability and Performance. µ Synthesis via D − K iterations. Reading Assignment

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      Source URL: control.lth.se

      Language: English - Date: 2015-05-10 13:39:21
        4Sampling Algorithms to Update Truncated SVD Ichitaro Yamazaki, Stanimire Tomov, and Jack Dongarra University of Tennessee, Knoxville, Tennessee, U.S.A. Abstract— A truncated singular value decomposition (SVD) is a powe

        Sampling Algorithms to Update Truncated SVD Ichitaro Yamazaki, Stanimire Tomov, and Jack Dongarra University of Tennessee, Knoxville, Tennessee, U.S.A. Abstract— A truncated singular value decomposition (SVD) is a powe

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        Source URL: icl.cs.utk.edu

        Language: English - Date: 2017-12-18 16:09:27
          5Orthogonal Matrices and the Singular Value Decomposition Carlo Tomasi The first Section below extends to m × n matrices the results on orthogonality and projection we have previously seen for vectors. The Sections there

          Orthogonal Matrices and the Singular Value Decomposition Carlo Tomasi The first Section below extends to m × n matrices the results on orthogonality and projection we have previously seen for vectors. The Sections there

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          Source URL: www.cs.duke.edu

          - Date: 2013-09-16 16:20:25
            6Using Singular Value Decomposition to Parameterize State-Dependent Model Errors Christopher M. Danforth∗ Department of Mathematics and Statistics, University of Vermont Burlington, VTEugenia Kalnay

            Using Singular Value Decomposition to Parameterize State-Dependent Model Errors Christopher M. Danforth∗ Department of Mathematics and Statistics, University of Vermont Burlington, VTEugenia Kalnay

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            Source URL: www.weatherchaos.umd.edu

            - Date: 2007-09-04 13:55:34
              7CS168: The Modern Algorithmic Toolbox Lecture #9: The Singular Value Decomposition (SVD) and Low-Rank Matrix Approximations Tim Roughgarden & Gregory Valiant∗ April 25, 2016

              CS168: The Modern Algorithmic Toolbox Lecture #9: The Singular Value Decomposition (SVD) and Low-Rank Matrix Approximations Tim Roughgarden & Gregory Valiant∗ April 25, 2016

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              Source URL: theory.stanford.edu

              - Date: 2016-06-04 09:49:44
                8Spectral Graph Theory and Applications  WSProblem Set 1 Due: Nov. 25

                Spectral Graph Theory and Applications WSProblem Set 1 Due: Nov. 25

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                Source URL: resources.mpi-inf.mpg.de

                Language: English - Date: 2011-11-14 10:39:49
                9103  Documenta Math. Dynamical Symmetries in Supersymmetric Matrix1

                103 Documenta Math. Dynamical Symmetries in Supersymmetric Matrix1

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                Source URL: documenta.sagemath.org

                Language: English - Date: 2009-02-25 10:07:02
                10Microsoft Word - Structures2007SysID-Submitted.doc

                Microsoft Word - Structures2007SysID-Submitted.doc

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                Source URL: nees.ucla.edu

                Language: English - Date: 2012-09-04 16:08:12