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    <title>Auteurs : Pakize Taylan</title>
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    <description>Publications of Auteurs Pakize Taylan</description>
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      <title>Approximation of Stochastic Differential Equations by Additive Models Using Splines and Conic Programming</title>
      <link>http://popups.lib.uliege.be/1373-5411/index.php?id=3272</link>
      <description>Stochastic differential equations are widely used to model noise-affected phenomena in nature, technology and economy (Kloeden et al., 1994). As these equations are usually hard to represent by a computer and hard to resolve we express them in simplified manner. We introduce an approximation by discretization and additive models based on splines. Then, we construct a penalized residual sum of squares (PRSS) for this model. We show when the related minimization program can be written as a Tikhonov regularization problem (ridge regression), and we treat it using continuous optimization techniques. In particular, we apply the elegant framework of conic quadratic programming. Convex optimization problems are very well-structured, resembling linear programs and permit the use of interior point methods (Nesterov &amp;amp; Nemirovskii, 1993). </description>
      <pubDate>Fri, 13 Sep 2024 13:53:07 +0200</pubDate>
      <lastBuildDate>Fri, 13 Sep 2024 13:53:16 +0200</lastBuildDate>
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