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Proximal Operator of Quotient Functions with Application to a Feasibility Problem in Query Optimization

Abstract : In this paper we determine the proximity functions of the sum and the maximum of componentwise (reciprocal) quotients of positive vectors. For the sum of quotients, denoted by $Q_1$, the proximity function is just a componentwise shrinkage function which we call q-shrinkage. This is similar to the proximity function of the ℓ1-norm which is given by componentwise soft shrinkage. For the maximum of quotients $Q_∞$, the proximal function can be computed by first order primal dual methods involving epigraphical projections. The proximity functions of $Q_ν$ , $ν = 1,∞$ are applied to solve convex problems of the form $argmin_x Q _ν ( Ax/b )$ subject to $x ≥ 0$, $1^\top x ≤ 1$. Such problems are of interest in selectivity estimation for cost-based query optimizers in database management systems.
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https://hal.archives-ouvertes.fr/hal-00942453
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Submitted on : Saturday, February 21, 2015 - 6:37:21 PM
Last modification on : Saturday, January 15, 2022 - 3:58:08 AM
Long-term archiving on: : Sunday, April 16, 2017 - 10:26:15 AM

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Guido Moerkotte, Martin Montag, Audrey Repetti, Gabriele Steidl. Proximal Operator of Quotient Functions with Application to a Feasibility Problem in Query Optimization. Journal of Computational and Applied Mathematics, Elsevier, 2015, 285, pp.243-255. ⟨10.1016/j.cam.2015.02.030⟩. ⟨hal-00942453v2⟩

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