Search Results - "WALKER, Homer F"

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  1. 1

    ANDERSON ACCELERATION FOR FIXED-POINT ITERATIONS by WALKER, HOMER F., NI, PENG

    Published in SIAM journal on numerical analysis (01-01-2011)
    “…This paper concerns an acceleration method for fixed-point iterations that originated in work of D. G. Anderson [J. Assoc. Comput. Mach., 12 (1965), pp…”
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  2. 2

    Anderson acceleration and application to the three-temperature energy equations by An, Hengbin, Jia, Xiaowei, Walker, Homer F.

    Published in Journal of computational physics (15-10-2017)
    “…The Anderson acceleration method is an algorithm for accelerating the convergence of fixed-point iterations, including the Picard method. Anderson acceleration…”
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  3. 3

    Globalization Techniques for Newton-Krylov Methods and Applications to the Fully Coupled Solution of the Navier-Stokes Equations by Pawlowski, Roger P., Shadid, John N., Simonis, Joseph P., Walker, Homer F.

    Published in SIAM review (01-12-2006)
    “…A Newton-Krylov method is an implementation of Newton's method in which a Krylov subspace method is used to solve approximately the linear subproblems that…”
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  4. 4

    Inexact Newton Dogleg Methods by Pawlowski, Roger P., Simonis, Joseph P., Walker, Homer F., Shadid, John N.

    Published in SIAM journal on numerical analysis (01-01-2008)
    “…The dogleg method is a classical trust-region technique for globalizing Newton's method. While it is widely used in optimization, including large-scale…”
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  5. 5

    On Using Approximate Finite Differences in Matrix-Free Newton-Krylov Methods by Brown, Peter N., Walker, Homer F., Wasyk, Rebecca, Woodward, Carol S.

    Published in SIAM journal on numerical analysis (01-01-2008)
    “…A Newton-Krylov method is an implementation of Newton's method in which a Krylov subspace method is used to solve approximately the linear systems that…”
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  6. 6

    An Inexact Newton Method for Fully Coupled Solution of the Navier–Stokes Equations with Heat and Mass Transport by Shadid, John N., Tuminaro, Ray S., Walker, Homer F.

    Published in Journal of computational physics (01-10-1997)
    “…The solution of the governing steady transport equations for momentum, heat and mass transfer in flowing fluids can be very difficult. These difficulties arise…”
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  7. 7

    Mixture Densities, Maximum Likelihood and the Em Algorithm by Redner, Richard A., Walker, Homer F.

    Published in SIAM review (01-04-1984)
    “…The problem of estimating the parameters which determine a mixture density has been the subject of a large, diverse body of literature spanning nearly ninety…”
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  8. 8

    Residual smoothing and peak/plateau behavior in Krylov subspace methods by Walker, Homer F.

    Published in Applied numerical mathematics (01-12-1995)
    “…Recent results on residual smoothing are reviewed, and it is observed that certain of these are equivalent to results obtained by different means that relate…”
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  9. 9

    Least-Change Secant Update Methods for Underdetermined Systems by Walker, Homer F., Watson, Layne T.

    Published in SIAM journal on numerical analysis (01-10-1990)
    “…Least-change secant updates for nonsquare matrices have been addressed recently in [6]. Here the use of these updates in iterative procedures for the numerical…”
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  10. 10

    A new adaptive GMRES algorithm for achieving high accuracy by Sosonkina, Maria, Watson, Layne T., Kapania, Rakesh K., Walker, Homer F.

    Published in Numerical linear algebra with applications (01-07-1998)
    “…GMRES(k) is widely used for solving non‐symmetric linear systems. However, it is inadequate either when it converges only for k close to the problem size or…”
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  11. 11

    Convergence Theorems for Least-Change Secant Update Methods by Dennis, J. E., Walker, Homer F.

    Published in SIAM journal on numerical analysis (01-12-1981)
    “…The purpose of this paper is to present a convergence analysis of least change secant methods in which part of the derivative matrix being approximated is…”
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  12. 12

    Least-Change Secant Updates of Nonsquare Matrices by Bourji, Samih K., Walker, Homer F.

    Published in SIAM journal on numerical analysis (01-10-1990)
    “…The notion of least-change secant updates is extended to apply to nonsquare matrices in a way appropriate for quasi-Newton methods used to solve systems of…”
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    On Backtracking Failure in Newton–GMRES Methods with a Demonstration for the Navier–Stokes Equations by Tuminaro, Raymond S., Walker, Homer F., Shadid, John N.

    Published in Journal of computational physics (10-08-2002)
    “…In an earlier study of inexact Newton methods, we pointed out that certain counterintuitive behavior may occur when applying residual backtracking to the…”
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  16. 16

    An Iterative Procedure for Obtaining Maximum-Likelihood Estimates of the Parameters for a Mixture of Normal Distributions by Peters, B. Charles, Walker, Homer F.

    Published in SIAM journal on applied mathematics (01-09-1978)
    “…This paper addresses the problem of obtaining numerically maximum-likelihood estimates of the parameters for a mixture of normal distributions. In recent…”
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  17. 17

    Least-Change Sparse Secant Update Methods with Inaccurate Secant Conditions by Dennis, J. E., Walker, Homer F.

    Published in SIAM journal on numerical analysis (01-08-1985)
    “…We investigate the role of the secant or quasi-Newton condition in the sparse Broyden or Schubert update method for solving systems of nonlinear equations…”
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    The Numerical Evaluation of the Maximum-Likelihood Estimate of a Subset of Mixture Proportions by Peters, B. Charles, Walker, Homer F.

    Published in SIAM journal on applied mathematics (01-11-1978)
    “…In this note, we give necessary and sufficient conditions for a maximum-likelihood estimate of a subset of the proportions in a mixture of specified…”
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  20. 20

    On Minimizing the Probability of Misclassification for Linear Feature Selection by Guseman, L. F., Peters, B. Charles, Walker, Homer F.

    Published in The Annals of statistics (01-05-1975)
    “…We describe an approach to linear feature selection for n-dimensional normally distributed observation vectors which belong to one of m populations. More…”
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