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          <dc:title>On Geodesically Convex Formulations for the Brascamp-Lieb Constant</dc:title>
          <dc:creator>Sra, Suvrit</dc:creator>
          <dc:creator>Vishnoi, Nisheeth K.</dc:creator>
          <dc:creator>Yildiz, Ozan</dc:creator>
          <dc:subject>Geodesic convexity</dc:subject>
          <dc:subject>positive definite cone</dc:subject>
          <dc:subject>geodesics</dc:subject>
          <dc:subject>Brascamp-Lieb constant</dc:subject>
          <dc:description>We consider two non-convex formulations for computing the optimal constant in the Brascamp-Lieb inequality corresponding to a given datum and show that they are geodesically log-concave on the manifold of positive definite matrices endowed with the Riemannian metric corresponding to the Hessian of the log-determinant function. The first formulation is present in the work of Lieb [Lieb, 1990] and the second is new and inspired by the work of Bennett et al. [Bennett et al., 2008]. Recent work of Garg et al. [Ankit Garg et al., 2017] also implies a geodesically log-concave formulation of the Brascamp-Lieb constant through a reduction to the operator scaling problem. However, the dimension of the arising optimization problem in their reduction depends exponentially on the number of bits needed to describe the Brascamp-Lieb datum. The formulations presented here have dimensions that are polynomial in the bit complexity of the input datum.</dc:description>
          <dc:publisher>Schloss Dagstuhl – Leibniz-Zentrum für Informatik</dc:publisher>
          <dc:contributor>Suvrit Sra and Nisheeth K. Vishnoi and Ozan Yildiz</dc:contributor>
          <dc:date>2018</dc:date>
          <dc:relation>Is Part Of LIPIcs, Volume 116, Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2018)</dc:relation>
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          <dc:identifier>doi:10.4230/LIPIcs.APPROX-RANDOM.2018.25</dc:identifier>
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          <dc:language>eng</dc:language>
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