Approximations of

Results: 293



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51Submitted to Statistical Science  Models as Approximations — A Conspiracy of Random Regressors and Model Misspecification Against

Submitted to Statistical Science Models as Approximations — A Conspiracy of Random Regressors and Model Misspecification Against

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Source URL: www-stat.wharton.upenn.edu

Language: English - Date: 2016-03-21 09:50:15
    52Markov chain approximations to non-symmetric diffusions with bounded coefficients Takashi Kumagai Kyoto University We consider a certain class of non-symmetric Markov chains and obtain heat kernel bounds and parabolic Ha

    Markov chain approximations to non-symmetric diffusions with bounded coefficients Takashi Kumagai Kyoto University We consider a certain class of non-symmetric Markov chains and obtain heat kernel bounds and parabolic Ha

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    Source URL: icsaa.iam.uni-bonn.de

    - Date: 2012-11-26 04:39:27
      53Anna Skripka* (). Perturbation of operator functions. The talk will discuss Taylor-like approximations for functions of operators. (Received September 21,

      Anna Skripka* (). Perturbation of operator functions. The talk will discuss Taylor-like approximations for functions of operators. (Received September 21,

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      Source URL: jointmathematicsmeetings.org

      - Date: 2012-09-23 00:40:22
        54Improved Mean and Variance Approximations for Belief Net Responses via Network Doubling Peter Hooper Yasin Abbasi-Yadkori, Russ Greiner, Bret Hoehn Dept of Mathematical & Statistical Sciences

        Improved Mean and Variance Approximations for Belief Net Responses via Network Doubling Peter Hooper Yasin Abbasi-Yadkori, Russ Greiner, Bret Hoehn Dept of Mathematical & Statistical Sciences

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        Source URL: webdocs.cs.ualberta.ca

        Language: English - Date: 2009-08-28 21:02:53
        55Semidefinite approximations of projections and polynomial images of semialgebraic sets V. Magron, D. Henrion, J.B. Lasserre LAAS-CNRS 7 avenue du colonel Roche, FToulouse, France

        Semidefinite approximations of projections and polynomial images of semialgebraic sets V. Magron, D. Henrion, J.B. Lasserre LAAS-CNRS 7 avenue du colonel Roche, FToulouse, France

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        Source URL: www.lifl.fr

        Language: English
          56Rough Burgers-like equations and their approximations Hendrik Weber Warwick University In this talk we discuss stochastic PDEs of the type du(t, x) = ∂xx u(t, x) +  

          Rough Burgers-like equations and their approximations Hendrik Weber Warwick University In this talk we discuss stochastic PDEs of the type du(t, x) = ∂xx u(t, x) +  

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          Source URL: icsaa.iam.uni-bonn.de

          - Date: 2012-11-26 04:39:28
            57GUARANTEED QUALITY APPROXIMATIONS FOR MEDIAL AXIS OF IMPLICIT PLANAR CURVES MICHAEL BURR∗ AND DAVID LETSCHER† Abstract. We apply subdivision methods to estimate the medial axis for a region bounded by an implicit cur

            GUARANTEED QUALITY APPROXIMATIONS FOR MEDIAL AXIS OF IMPLICIT PLANAR CURVES MICHAEL BURR∗ AND DAVID LETSCHER† Abstract. We apply subdivision methods to estimate the medial axis for a region bounded by an implicit cur

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            Source URL: fwcg14.cse.uconn.edu

            Language: English - Date: 2014-10-29 21:34:50
              58Submitted to Statistical Science  Models as Approximations — A Conspiracy of Random Regressors and Model Deviations Against Classical

              Submitted to Statistical Science Models as Approximations — A Conspiracy of Random Regressors and Model Deviations Against Classical

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              Source URL: www-stat.wharton.upenn.edu

              Language: English - Date: 2015-09-24 15:33:15
                59IMA Journal of Numerical Analysis, Superconvergent Recovery of the Gradient from Piecewise Linear Finite-element Approximations N I C K LEVINE

                IMA Journal of Numerical Analysis, Superconvergent Recovery of the Gradient from Piecewise Linear Finite-element Approximations N I C K LEVINE

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                Source URL: www.nicklevine.org

                Language: English - Date: 2014-06-14 06:16:53
                  602. Effective Approximations of Matching Priors  1. Summary How can we achieve truly robust dense, real-time matching? The strong priors generally available on image correspondence problems, are often used partially and p

                  2. Effective Approximations of Matching Priors 1. Summary How can we achieve truly robust dense, real-time matching? The strong priors generally available on image correspondence problems, are often used partially and p

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                  Source URL: www.margaritachli.com

                  Language: English - Date: 2011-06-29 13:14:06