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          <dc:title>Convergence Thresholds of Newton's Method for Monotone Polynomial Equations</dc:title>
          <dc:creator>Esparza, Javier</dc:creator>
          <dc:creator>Kiefer, Stefan</dc:creator>
          <dc:creator>Luttenberger, Michael</dc:creator>
          <dc:subject>Newton's Method</dc:subject>
          <dc:subject>Fixed-Point Equations</dc:subject>
          <dc:subject>Formal Verification of Software</dc:subject>
          <dc:subject>Probabilistic Pushdown Systems</dc:subject>
          <dc:description>Monotone systems of polynomial equations (MSPEs) are systems of&#13;
   fixed-point equations $X_1 = f_1(X_1, ldots, X_n),$ $ldots, X_n =&#13;
   f_n(X_1, ldots, X_n)$ where each $f_i$ is a polynomial with&#13;
   positive real coefficients.  The question of computing the least&#13;
   non-negative solution of a given MSPE $vec X = vec f(vec X)$&#13;
   arises naturally in the analysis of stochastic models such as&#13;
   stochastic context-free grammars, probabilistic pushdown automata,&#13;
   and back-button processes.  Etessami and Yannakakis have recently&#13;
   adapted Newton's iterative method to MSPEs.  In a previous paper we&#13;
   have proved the existence of a threshold $k_{vec f}$ for strongly&#13;
   connected MSPEs, such that after $k_{vec f}$ iterations of&#13;
   Newton's method each new iteration computes at least 1 new bit of&#13;
   the solution.  However, the proof was purely existential.  In this&#13;
   paper we give an upper bound for $k_{vec f}$ as a function of the&#13;
   minimal component of the least fixed-point $muvec f$ of $vec&#13;
   f(vec X)$.  Using this result we show that $k_{vec f}$ is at most&#13;
   single exponential resp.  linear for strongly connected MSPEs&#13;
   derived from probabilistic pushdown automata resp.  from&#13;
   back-button processes.  Further, we prove the existence of a&#13;
   threshold for arbitrary MSPEs after which each new iteration&#13;
   computes at least $1/w2^h$ new bits of the solution, where $w$ and&#13;
   $h$ are the width and height of the DAG of strongly connected&#13;
   components.</dc:description>
          <dc:publisher>Schloss Dagstuhl – Leibniz-Zentrum für Informatik</dc:publisher>
          <dc:contributor>Javier Esparza and Stefan Kiefer and Michael Luttenberger</dc:contributor>
          <dc:date>2008</dc:date>
          <dc:relation>Is Part Of LIPIcs, Volume 1, 25th International Symposium on Theoretical Aspects of Computer Science (2008)</dc:relation>
          <dc:type>InProceedings</dc:type>
          <dc:type>Text</dc:type>
          <dc:type>doc-type:ResearchArticle</dc:type>
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          <dc:format>application/pdf</dc:format>
          <dc:identifier>doi:10.4230/LIPIcs.STACS.2008.1351</dc:identifier>
          <dc:identifier>urn:nbn:de:0030-drops-13516</dc:identifier>
          <dc:identifier>https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.STACS.2008.1351</dc:identifier>
          <dc:language>eng</dc:language>
          <dc:rights>https://creativecommons.org/licenses/by-nd/3.0/legalcode</dc:rights>
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