Relevant bibliographies by topics / Newton-type method

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Newton-type method'

Author: Grafiati
Published: 10 March 2023

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Journal articles on the topic "Newton-type method"

1

Fischer, A. "A special newton-type optimization method." Optimization 24, no. 3-4 (January 1992): 269–84. http://dx.doi.org/10.1080/02331939208843795.

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Păvăloiu, Ion, and Emil Cătinaş. "On an Aitken–Newton type method." Numerical Algorithms 62, no. 2 (May 6, 2012): 253–60. http://dx.doi.org/10.1007/s11075-012-9577-7.

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Păvăloiu, I., and E. Cătinaş. "On a Newton–Steffensen type method." Applied Mathematics Letters 26, no. 6 (June 2013): 659–63. http://dx.doi.org/10.1016/j.aml.2013.01.003.

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Ramm, A. G. "On the DSM Newton-type method." Journal of Applied Mathematics and Computing 38, no. 1-2 (June 9, 2011): 523–33. http://dx.doi.org/10.1007/s12190-011-0494-z.

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Jnawali, Jivandhar. "New Modified Newton Type Iterative Methods." Nepal Journal of Mathematical Sciences 2, no. 1 (April 30, 2021): 17–24. http://dx.doi.org/10.3126/njmathsci.v2i1.36559.

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In this work, we present two Newton type iterative methods for finding the solution of nonlinear equations of single variable. One is obtained as variant of McDougall and Wotherspoon method, and another is obtained by amalgamation of Potra and Pta’k method and our newly introduced method. The order of convergence of these methods are 1 + √2 and 3.5615. Some numerical examples are given to compare the performance of these methods with some similar existing methods.
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PAVALOIU, ION. "On an Aitken-Steffensen-Newton type method." Carpathian Journal of Mathematics 34, no. 1 (2018): 85–92. http://dx.doi.org/10.37193/cjm.2018.01.09.

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We consider an Aitken-Steffensen type method in which the nodes are controlled by Newton and two-step Newton iterations. We prove a local convergence result showing the q-convergence order 7 of the iterations. Under certain supplementary conditions, we obtain monotone convergence of the iterations, providing an alternative to the usual ball attraction theorems. Numerical examples show that this method may, in some cases, have larger (possibly sided) convergence domains than other methods with similar convergence orders.
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Vijesh, V. Antony, and P. V. Subrahmanyam. "A Newton-type method and its application." International Journal of Mathematics and Mathematical Sciences 2006 (2006): 1–9. http://dx.doi.org/10.1155/ijmms/2006/23674.

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We prove an existence and uniqueness theorem for solving the operator equationF(x)+G(x)=0, whereFis a continuous and Gâteaux differentiable operator and the operatorGsatisfies Lipschitz condition on an open convex subset of a Banach space. As corollaries, a recent theorem of Argyros (2003) and the classical convergence theorem for modified Newton iterates are deduced. We further obtain an existence theorem for a class of nonlinear functional integral equations involving the Urysohn operator.
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Bayrak, Mine Aylin, Ali Demir, and Ebru Ozbilge. "On Fractional Newton-Type Method for Nonlinear Problems." Journal of Mathematics 2022 (November 21, 2022): 1–10. http://dx.doi.org/10.1155/2022/7070253.

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The current manuscript is concerned with the development of the Newton–Raphson method, playing a significant role in mathematics and various other disciplines such as optimization, by using fractional derivatives and fractional Taylor series expansion. The development and modification of the Newton–Raphson method allow us to establish two new methods, which are called first- and second-order fractional Newton–Raphson (FNR) methods. We provide convergence analysis of first- and second-order fractional methods and give a general condition for the convergence of higher-order FNR. Finally, some illustrative examples are considered to confirm the accuracy and effectiveness of both methods.
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Jnawali, Jivandhar, and Chet Raj Bhatta. "Iterative Methods for Solving Nonlinear Equations with Fourth-Order Convergence." Tribhuvan University Journal 30, no. 2 (December 1, 2016): 65–72. http://dx.doi.org/10.3126/tuj.v30i2.25548.

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In this paper, we obtain fourth order iterative method for solving nonlinear equations by combining arithmetic mean Newton method, harmonic mean Newton method and midpoint Newton method uniquely. Also, some variant of Newton type methods based on inverse function have been developed. These methods are free from second order derivatives.
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Zhao, Wan-Chen, and Xin-Hui Shao. "New matrix splitting iteration method for generalized absolute value equations." AIMS Mathematics 8, no. 5 (2023): 10558–78. http://dx.doi.org/10.3934/math.2023536.

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<abstract><p>In this paper, a relaxed Newton-type matrix splitting (RNMS) iteration method is proposed for solving the generalized absolute value equations, which includes the Picard method, the modified Newton-type (MN) iteration method, the shift splitting modified Newton-type (SSMN) iteration method and the Newton-based matrix splitting (NMS) iteration method. We analyze the sufficient convergence conditions of the RNMS method. Lastly, the efficiency of the RNMS method is analyzed by numerical examples involving symmetric and non-symmetric matrices.</p></abstract>
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Dissertations / Theses on the topic "Newton-type method"

1

Herrich, Markus. "Local Convergence of Newton-type Methods for Nonsmooth Constrained Equations and Applications." Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2015. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-159569.

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In this thesis we consider constrained systems of equations. The focus is on local Newton-type methods for the solution of constrained systems which converge locally quadratically under mild assumptions implying neither local uniqueness of solutions nor differentiability of the equation function at solutions. The first aim of this thesis is to improve existing local convergence results of the constrained Levenberg-Marquardt method. To this end, we describe a general Newton-type algorithm. Then we prove local quadratic convergence of this general algorithm under the same four assumptions which were recently used for the local convergence analysis of the LP-Newton method. Afterwards, we show that, besides the LP-Newton method, the constrained Levenberg-Marquardt method can be regarded as a special realization of the general Newton-type algorithm and therefore enjoys the same local convergence properties. Thus, local quadratic convergence of a nonsmooth constrained Levenberg-Marquardt method is proved without requiring conditions implying the local uniqueness of solutions. As already mentioned, we use four assumptions for the local convergence analysis of the general Newton-type algorithm. The second aim of this thesis is a detailed discussion of these convergence assumptions for the case that the equation function of the constrained system is piecewise continuously differentiable. Some of the convergence assumptions seem quite technical and difficult to check. Therefore, we look for sufficient conditions which are still mild but which seem to be more familiar. We will particularly prove that the whole set of the convergence assumptions holds if some set of local error bound conditions is satisfied and in addition the feasible set of the constrained system excludes those zeros of the selection functions which are not zeros of the equation function itself, at least in a sufficiently small neighborhood of some fixed solution. We apply our results to constrained systems arising from complementarity systems, i.e., systems of equations and inequalities which contain complementarity constraints. Our new conditions are discussed for a suitable reformulation of the complementarity system as constrained system of equations by means of the minimum function. In particular, it will turn out that the whole set of the convergence assumptions is actually implied by some set of local error bound conditions. In addition, we provide a new constant rank condition implying the whole set of the convergence assumptions. Particularly, we provide adapted formulations of our new conditions for special classes of complementarity systems. We consider Karush-Kuhn-Tucker (KKT) systems arising from optimization problems, variational inequalities, or generalized Nash equilibrium problems (GNEPs) and Fritz-John (FJ) systems arising from GNEPs. Thus, we obtain for each problem class conditions which guarantee local quadratic convergence of the general Newton-type algorithm and its special realizations to a solution of the particular problem. Moreover, we prove for FJ systems of GNEPs that generically some full row rank condition is satisfied at any solution of the FJ system of a GNEP. The latter condition implies the whole set of the convergence assumptions if the functions which characterize the GNEP are sufficiently smooth. Finally, we describe an idea for a possible globalization of our Newton-type methods, at least for the case that the constrained system arises from a certain smooth reformulation of the KKT system of a GNEP. More precisely, a hybrid method is presented whose local part is the LP-Newton method. The hybrid method turns out to be, under appropriate conditions, both globally and locally quadratically convergent.
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Delbary, Fabrice. "Identification de fissures par ondes acoustiques." Paris 6, 2006. http://www.theses.fr/2006PA066605.

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Cette thèse porte sur le problème de reconstruction de fissures par ondes acoustiques. Le premier objectif consiste à développer une méthode d'inversion rapide utilisant un unique couple de données de Cauchy sur la frontière d'un domaine entourant la fissure sous l'hypothèse que la fissure cherchée est plane. L'utilisation de la fonctionnelle Écart à la Réciprocité nous fournit alors une méthode de reconstruction quasi explicite. Le second objectif consiste à trouver une méthode d'inversion pour le problème de Helmholtz en milieu inhomogène. L'utilisation de la fonctionnelle Écart à la Réciprocité combinée à une méthode de type "Sampling Method" permet alors la reconstruction de fissures de formes quelconques à partir de données en champ proche.
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Abbas, Boushra. "Méthode de Newton régularisée pour les inclusions monotones structurées : étude des dynamiques et algorithmes associés." Thesis, Montpellier, 2015. http://www.theses.fr/2015MONTS250/document.

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Cette thèse est consacrée à la recherche des zéros d'un opérateur maximal monotone structuré, à l'aide de systèmes dynamiques dissipatifs continus et discrets. Les solutions sont obtenues comme limites des trajectoires lorsque le temps t tend vers l'infini. On s'intéressera principalement aux dynamiques obtenues par régularisation de type Levenberg-Marquardt de la méthode de Newton. On décrira aussi les approches basées sur des dynamiques voisines.Dans un cadre Hilbertien, on s'intéresse à la recherche des zéros de l'opérateur maximal monotone structuré M = A + B, où A est un opérateur maximal monotone général et B est un opérateur monotone Lipschitzien. Nous introduisons des dynamiques continues et discrètes de type Newton régularisé faisant intervenir d'une façon séparée les résolvantes de l'opérateur A (implicites), et des évaluations de B (explicites). A l'aide de la représentation de Minty de l'opérateur A comme une variété Lipschitzienne, nous reformulons ces dynamiques sous une forme relevant du théorème de Cauchy-Lipschitz. Nous nous intéressons au cas particulier où A est le sous différentiel d'une fonction convexe, semi-continue inférieurement, et propre, et B est le gradient d'une fonction convexe, différentiable. Nous étudions le comportement asymptotique des trajectoires. Lorsque le terme de régularisation ne tend pas trop vite vers zéro, et en s'appuyant sur une analyse asymptotique de type Lyapunov, nous montrons la convergence des trajectoires. Par ailleurs, nous montrons la dépendance Lipschitzienne des trajectoires par rapport au terme de régularisation.Puis nous élargissons notre étude en considérant différentes classes de systèmes dynamiques visant à résoudre les inclusions monotones gouvernées par un opérateur maximal monotone structuré M = $partialPhi$+ B, où $partialPhi$ désigne le sous différentiel d'une fonction convexe, semicontinue inférieurement, et propre, et B est un opérateur monotone cocoercif. En s'appuyant sur une analyse asymptotique de type Lyapunov, nous étudions le comportement asymptotique des trajectoires de ces systèmes. La discrétisation temporelle de ces dynamiques fournit desalgorithmes forward-backward (certains nouveaux ).Finalement, nous nous intéressons à l'étude du comportement asymptotique des trajectoires de systèmes dynamiques de type Newton régularisé, dans lesquels on introduit un terme supplémentaire de viscosité évanescente de type Tikhonov. On obtient ainsi la sélection asymptotique d'une solution de norme minimale
This thesis is devoted to finding zeroes of structured maximal monotone operators, by using discrete and continuous dissipative dynamical systems. The solutions are obtained as the limits of trajectories when the time t tends towards infinity.We pay special attention to the dynamics that are obtained by Levenberg-Marquardt regularization of Newton's method. We also revisit the approaches based on some related dynamical systems.In a Hilbert framework, we are interested in finding zeroes of a structured maximal monotone operator M = A + B, where A is a general maximal monotone operator, and B is monotone and locally Lipschitz continuous. We introduce discrete and continuous dynamical systems which are linked to Newton's method. They involve separately B and the resolvents of A, and are designed to splitting methods. Based on the Minty representation of A as a Lipschitz manifold, we show that these dynamics can be formulated as differential systems, which are relevant to the Cauchy-Lipschitz theorem. We focus on the particular case where A is the subdifferential of a convex lower semicontinuous proper function, and B is the gradient of a convex, continuously differentiable function. We study the asymptotic behavior of trajectories. When the regularization parameter does not tend to zero too rapidly, and by using Lyapunov asymptotic analysis, we show the convergence of trajectories. Besides, we show the Lipschitz continuous dependence of the solution with respect to the regularization term.Then we extend our study by considering various classes of dynamical systems which aim at solving inclusions governed by structured monotone operators M = $partialPhi$+ B, where $partialPhi$ is the subdifferential of a convex lower semicontinuous function, and B is a monotone cocoercive operator. By a Lyapunov analysis, we show the convergence properties of the orbits of these systems. The time discretization of these dynamics gives various forward-backward splittingmethods (some new).Finally, we focus on the study of the asymptotic behavior of trajectories of the regularized Newton dynamics, in which we introduce an additional vanishing Tikhonov-like viscosity term.We thus obtain the asymptotic selection of the solution of minimal norm
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4

Fountoulakis, Kimon. "Higher-order methods for large-scale optimization." Thesis, University of Edinburgh, 2015. http://hdl.handle.net/1842/15797.

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There has been an increased interest in optimization for the analysis of large-scale data sets which require gigabytes or terabytes of data to be stored. A variety of applications originate from the fields of signal processing, machine learning and statistics. Seven representative applications are described below. - Magnetic Resonance Imaging (MRI): A medical imaging tool used to scan the anatomy and the physiology of a body. - Image inpainting: A technique for reconstructing degraded parts of an image. - Image deblurring: Image processing tool for removing the blurriness of a photo caused by natural phenomena, such as motion. - Radar pulse reconstruction. - Genome-Wide Association study (GWA): DNA comparison between two groups of people (with/without a disease) in order to investigate factors that a disease depends on. - Recommendation systems: Classification of data (i.e., music or video) based on user preferences. - Data fitting: Sampled data are used to simulate the behaviour of observed quantities. For example estimation of global temperature based on historic data. Large-scale problems impose restrictions on methods that have been so far employed. The new methods have to be memory efficient and ideally, within seconds they should offer noticeable progress towards a solution. First-order methods meet some of these requirements. They avoid matrix factorizations, they have low memory requirements, additionally, they sometimes offer fast progress in the initial stages of optimization. Unfortunately, as demonstrated by numerical experiments in this thesis, first-order methods miss essential information about the conditioning of the problems, which might result in slow practical convergence. The main advantage of first-order methods which is to rely only on simple gradient or coordinate updates becomes their essential weakness. We do not think this inherent weakness of first-order methods can be remedied. For this reason, the present thesis aims at the development and implementation of inexpensive higher-order methods for large-scale problems.
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Ueda, Kenji. "STUDIES ON REGULARIZED NEWTON-TYPE METHODS FOR UNCONSTRAINED MINIMIZATION PROBLEMS AND THEIR GLOBAL COMPLEXITY BOUNDS." 京都大学 (Kyoto University), 2012. http://hdl.handle.net/2433/157479.

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6

Herrich, Markus [Verfasser], Andreas [Akademischer Betreuer] Fischer, and Christian [Akademischer Betreuer] Kanzow. "Local Convergence of Newton-type Methods for Nonsmooth Constrained Equations and Applications / Markus Herrich. Gutachter: Andreas Fischer ; Christian Kanzow. Betreuer: Andreas Fischer." Dresden : Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2015. http://d-nb.info/1069092800/34.

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Herrich, Markus Verfasser], Andreas [Akademischer Betreuer] [Fischer, and Christian [Akademischer Betreuer] Kanzow. "Local Convergence of Newton-type Methods for Nonsmooth Constrained Equations and Applications / Markus Herrich. Gutachter: Andreas Fischer ; Christian Kanzow. Betreuer: Andreas Fischer." Dresden : Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2015. http://d-nb.info/1069092800/34.

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Herrich, Markus. "Local Convergence of Newton-type Methods for Nonsmooth Constrained Equations and Applications." Doctoral thesis, 2014. https://tud.qucosa.de/id/qucosa%3A28495.

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In this thesis we consider constrained systems of equations. The focus is on local Newton-type methods for the solution of constrained systems which converge locally quadratically under mild assumptions implying neither local uniqueness of solutions nor differentiability of the equation function at solutions. The first aim of this thesis is to improve existing local convergence results of the constrained Levenberg-Marquardt method. To this end, we describe a general Newton-type algorithm. Then we prove local quadratic convergence of this general algorithm under the same four assumptions which were recently used for the local convergence analysis of the LP-Newton method. Afterwards, we show that, besides the LP-Newton method, the constrained Levenberg-Marquardt method can be regarded as a special realization of the general Newton-type algorithm and therefore enjoys the same local convergence properties. Thus, local quadratic convergence of a nonsmooth constrained Levenberg-Marquardt method is proved without requiring conditions implying the local uniqueness of solutions. As already mentioned, we use four assumptions for the local convergence analysis of the general Newton-type algorithm. The second aim of this thesis is a detailed discussion of these convergence assumptions for the case that the equation function of the constrained system is piecewise continuously differentiable. Some of the convergence assumptions seem quite technical and difficult to check. Therefore, we look for sufficient conditions which are still mild but which seem to be more familiar. We will particularly prove that the whole set of the convergence assumptions holds if some set of local error bound conditions is satisfied and in addition the feasible set of the constrained system excludes those zeros of the selection functions which are not zeros of the equation function itself, at least in a sufficiently small neighborhood of some fixed solution. We apply our results to constrained systems arising from complementarity systems, i.e., systems of equations and inequalities which contain complementarity constraints. Our new conditions are discussed for a suitable reformulation of the complementarity system as constrained system of equations by means of the minimum function. In particular, it will turn out that the whole set of the convergence assumptions is actually implied by some set of local error bound conditions. In addition, we provide a new constant rank condition implying the whole set of the convergence assumptions. Particularly, we provide adapted formulations of our new conditions for special classes of complementarity systems. We consider Karush-Kuhn-Tucker (KKT) systems arising from optimization problems, variational inequalities, or generalized Nash equilibrium problems (GNEPs) and Fritz-John (FJ) systems arising from GNEPs. Thus, we obtain for each problem class conditions which guarantee local quadratic convergence of the general Newton-type algorithm and its special realizations to a solution of the particular problem. Moreover, we prove for FJ systems of GNEPs that generically some full row rank condition is satisfied at any solution of the FJ system of a GNEP. The latter condition implies the whole set of the convergence assumptions if the functions which characterize the GNEP are sufficiently smooth. Finally, we describe an idea for a possible globalization of our Newton-type methods, at least for the case that the constrained system arises from a certain smooth reformulation of the KKT system of a GNEP. More precisely, a hybrid method is presented whose local part is the LP-Newton method. The hybrid method turns out to be, under appropriate conditions, both globally and locally quadratically convergent.
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9

FRASCA, CACCIA GIANLUCA. "A new efficient implementation for HBVMs and their application to the semilinear wave equation." Doctoral thesis, 2015. http://hdl.handle.net/2158/992629.

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In this thesis we have provided a detailed description of the low-rank Runge-Kutta family of Hamiltonian Boundary Value Methods (HBVMs) for the numerical solution of Hamiltonian problems. In particular, we have studied in detail their main property: the conservation of polynomial Hamiltonians, which results into a practical conservation for generic suitably regular Hamiltonians. This property turns out to play a fundamental role in some problems where the error on the Hamiltonian, usually obtained even when using a symplectic method, would be not negligible to the point of affecting the dynamics of the numerical solution. The research developed in this thesis has addressed two main topics. The first one is a new procedure, based on a particular splitting of the matrix defining the method, which turns out to be more effective of the well-known blended-implementation, as well as of a classical fixed-point iteration when the problem at hand is stiff. This procedure has been applied also to second order problems with separable Hamiltonian function, resulting in a cheaper computational cost. The second topic addressed is the application of HBVMs for the full discretization of a method of lines approach to numerically solve Hamiltonian PDEs. In particular, we have considered the semilinear wave equation coupled with either periodic, Dirichlet or Neumann boundary conditions, and the application of a (practically) energy conserving HBVM method to the semi-discrete problem obtained by means of a second order finite-difference approximation in space. When the problem is coupled with periodic boundary conditions we have also considered the case of higher-order finite-difference spatial discretizations and the case when a Fourier-Galerkin method is used for the spatial semi-discretization. The proposed methods are able to provide a numerical solution such that the energy (which can be conserved or not, depending on the assigned boundary conditions) practically satisfies its prescribed variation in time. A few numerical tests for the sine-Gordon equation have given evidence that, for some problems, there is an effective advantage in using an energy-conserving method for the time integration, with respect to the use of a symplectic one. Moreover, even though HBVMs are implicit method, their computational cost for the considered problem turns out to be competitive even with respect to that of explicit solvers of the same order, which, furthermore, may suffer from stepsize restrictions due to stability reasons, whereas HBVMs are A-stable.
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Yusufu, Simayi. "Convergence rates for variational regularization of inverse problems in exponential families." Doctoral thesis, 2019. http://hdl.handle.net/21.11130/00-1735-0000-0005-1421-F.

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Books on the topic "Newton-type method"

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Izmailov, Alexey F., and Mikhail V. Solodov. Newton-Type Methods for Optimization and Variational Problems. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-04247-3.

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author, Solodov Mikhail V., ed. Newton-type methods for optimization and variational problems. Cham: Springer, 2014.

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Argyros, Ioannis K. Convergence and Applications of Newton-type Iterations. Springer, 2010.

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Convergence and Applications of Newton-type Iterations. Springer, 2008.

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Convergence and Applications of Newton-Type Iterations. Springer London, Limited, 2008.

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Verma, Ram U. Next Generation Newton-Type Methods. Nova Science Publishers, Incorporated, 2019.

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Next Generation Newton-Type Methods. Nova Science Publishers, Incorporated, 2019.

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Solodov, Mikhail V., and Alexey F. Izmailov. Newton-Type Methods for Optimization and Variational Problems. Springer International Publishing AG, 2016.

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Algebraic And Combinatorial Aspects Of Tropical Geometry Ciem Workshop On Tropical Geometry December 1216 2011 International Center For Mathematical Meetings Castro Urdiales Spain. American Mathematical Society, 2013.

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Book chapters on the topic "Newton-type method"

1

Nakao, Mitsuhiro T., Michael Plum, and Yoshitaka Watanabe. "Infinite-Dimensional Newton-Type Method." In Springer Series in Computational Mathematics, 73–101. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-7669-6_3.

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Novotny, Antonio André, Jan Sokołowski, and Antoni Żochowski. "A Newton-Type Method and Applications." In Applications of the Topological Derivative Method, 165–81. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-05432-8_10.

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Fischer, Andreas. "New Results on a Newton-Type Method for LCP." In Operations Research ’93, 165–68. Heidelberg: Physica-Verlag HD, 1994. http://dx.doi.org/10.1007/978-3-642-46955-8_43.

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Kanzow, Christian. "An Active Set-Type Newton Method for Constrained Nonlinear Systems." In Complementarity: Applications, Algorithms and Extensions, 179–200. Boston, MA: Springer US, 2001. http://dx.doi.org/10.1007/978-1-4757-3279-5_9.

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Pareth, Suresan, and Santhosh George. "Projection Scheme for Newton-Type Iterative Method for Lavrentiev Regularization." In Eco-friendly Computing and Communication Systems, 302–10. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-32112-2_36.

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Argyros, Ioannis K. "Two-Step Gauss-Newton Werner-Type Method for Least Squares Problems." In The Theory and Applications of Iteration Methods, 325–38. 2nd ed. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9781003128915-17.

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Meng, Ze-hong, Zhen-yu Zhao, and Guo-qiang He. "A Modification of Regularized Newton-Type Method for Nonlinear Ill-Posed Problems." In Lecture Notes in Computer Science, 295–304. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-11842-5_40.

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Dimitrova, N. S. "On Some Properties of an Interval Newton Type Method and its Modification." In Computing Supplementum, 21–32. Vienna: Springer Vienna, 1993. http://dx.doi.org/10.1007/978-3-7091-6918-6_3.

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Ghosh, Debdas. "A Davidon-Fletcher-Powell Type Quasi-Newton Method to Solve Fuzzy Optimization Problems." In Communications in Computer and Information Science, 232–45. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-4642-1_20.

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Sun, Li, and Liang Fang. "A Modified Newton-Type Method with Sixth-Order Convergence for Solving Nonlinear Equations." In Advances in Computer Science, Environment, Ecoinformatics, and Education, 470–73. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-23339-5_86.

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Conference papers on the topic "Newton-type method"

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Li, Tian, Anit Kumar Sahu, Manzil Zaheer, Maziar Sanjabi, Ameet Talwalkar, and Virginia Smithy. "FedDANE: A Federated Newton-Type Method." In 2019 53rd Asilomar Conference on Signals, Systems, and Computers. IEEE, 2019. http://dx.doi.org/10.1109/ieeeconf44664.2019.9049023.

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Cao, Ying, and Xiaofeng Wang. "A Newton-Type Iterative Method for Computing Matrix Sign Function." In 2022 International Conference on Cloud Computing, Big Data and Internet of Things (3CBIT). IEEE, 2022. http://dx.doi.org/10.1109/3cbit57391.2022.00081.

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Pang, D. Y., S. Q. Du, and J. J. Ju. "The Applications of A Newton-Type Method for Constrained Nonsmooth Equations." In 2015 International Conference on Artificial Intelligence and Industrial Engineering. Paris, France: Atlantis Press, 2015. http://dx.doi.org/10.2991/aiie-15.2015.141.

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Yunhong Hu and Liang Fang. "A seventh-order convergent Newton-type method for solving nonlinear equations." In 2010 Second International Conference on Computational Intelligence and Natural Computing (CINC). IEEE, 2010. http://dx.doi.org/10.1109/cinc.2010.5643798.

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Hermans, Ben, Andreas Themelis, and Panagiotis Patrinos. "QPALM: A Newton-type Proximal Augmented Lagrangian Method for Quadratic Programs." In 2019 IEEE 58th Conference on Decision and Control (CDC). IEEE, 2019. http://dx.doi.org/10.1109/cdc40024.2019.9030211.

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Akimova, E., and A. Skurydina. "A componentwise Newton type method for solving the structural inverse gravity problem." In 14th EAGE International Conference on Geoinformatics - Theoretical and Applied Aspects. Netherlands: EAGE Publications BV, 2015. http://dx.doi.org/10.3997/2214-4609.201412361.

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Meng, Zehong, and Zhenyu Zhao. "Newton-type method with double regularization parameters for nonlinear ill-posed problems." In 2009 IEEE International Conference on Intelligent Computing and Intelligent Systems (ICIS 2009). IEEE, 2009. http://dx.doi.org/10.1109/icicisys.2009.5358383.

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Bazzi, Ahmad, Dirk T. M. Slock, and Lisa Meilhac. "A Newton-type Forward Backward Greedy method for multi-snapshot compressed sensing." In 2017 51st Asilomar Conference on Signals, Systems, and Computers. IEEE, 2017. http://dx.doi.org/10.1109/acssc.2017.8335537.

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Meng, Zehong. "One Newton-type method for the regularization of nonlinear ill-posed problems." In 2011 International Conference on Multimedia Technology (ICMT). IEEE, 2011. http://dx.doi.org/10.1109/icmt.2011.6002227.

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Okamoto, Takashi. "Constrained optimization using the chaotic sequential quadratic approximation type Lagrange quasi-Newton method." In 2014 IEEE International Conference on Systems, Man and Cybernetics - SMC. IEEE, 2014. http://dx.doi.org/10.1109/smc.2014.6973967.

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Reports on the topic "Newton-type method"

1

Yamamoto, Tetsuro. Error Bounds for Newton-Like Methods Under Kantorovich Type Assumptions. Fort Belvoir, VA: Defense Technical Information Center, July 1985. http://dx.doi.org/10.21236/ada160994.

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