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      Local convergence of Levenberg-Marquardt methods under H\"{o}lder metric subregularity

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          Abstract

          We describe and analyse Levenberg-Marquardt methods for solving systems of nonlinear equations. More specifically, we first propose an adaptive formula for the Levenberg-Marquardt parameter and analyse the local convergence of the method under H\"{o}lder metric subregularity. We then introduce a bounded version of the Levenberg-Marquardt parameter and analyse the local convergence of the modified method under the \L ojasiewicz gradient inequality. We finally report encouraging numerical results confirming the theoretical findings for the problem of computing moiety conserved steady states in biochemical reaction networks. This problem can be cast as finding a solution of a system of nonlinear equations, where the associated mapping satisfies the H\"{o}lder metric subregularity assumption.

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          Error bounds in mathematical programming

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            Detection of stoichiometric inconsistencies in biomolecular models.

            Metabolic modelling provides a mathematically rigorous basis for system-level analysis of biochemical networks. However, the growing sizes of metabolic models can lead to serious problems in their construction and validation. In this work, we describe a relatively poorly investigated type of modelling error, called stoichiometric inconsistencies. These errors are caused by incorrect definitions of reaction stoichiometries and result in conflicts between two fundamental physical constraints to be satisfied by any valid metabolic model: positivity of molecular masses of all metabolites and mass conservation in all interconversions. We introduce formal definitions of stoichiometric inconsistencies, inconsistent net stoichiometries, elementary leakage modes and other important fundamental properties of incorrectly defined biomolecular networks. Algorithms are described for the verification of stoichiometric consistency of a model, detection of unconserved metabolites and inconsistent minimal net stoichiometries. The usefulness of these algorithms for effective resolving of inconsistencies and for detection of input errors is demonstrated on a published genome-scale metabolic model of Saccharomyces cerevisiae and one of Streptococcus agalactiae constructed using the KEGG database. http://mudshark.brookes.ac.uk/index.php/Albert_Gevorgyan.
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              On the Quadratic Convergence of the Levenberg-Marquardt Method without Nonsingularity Assumption

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                Author and article information

                Journal
                2017-03-21
                Article
                1703.07461
                5fba0224-56bc-4a6e-9042-9c7cb80ba971

                http://arxiv.org/licenses/nonexclusive-distrib/1.0/

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                Custom metadata
                65K05, 65K10, 90C26, 92C42
                33 pages, 10 figures
                q-bio.MN

                Molecular biology
                Molecular biology

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