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Proximal operator of quotient functions with application to a feasibility problem in query optimization

Authors :
Martin Montag
Gabriele Steidl
Audrey Repetti
Guido Moerkotte
Database Research Group [Mannheim]
Universität Mannheim [Mannheim]
University of Kaiserslautern [Kaiserslautern]
Laboratoire d'Informatique Gaspard-Monge (LIGM)
Centre National de la Recherche Scientifique (CNRS)-Fédération de Recherche Bézout-ESIEE Paris-École des Ponts ParisTech (ENPC)-Université Paris-Est Marne-la-Vallée (UPEM)
Publica
Source :
Journal of Computational and Applied Mathematics, Journal of Computational and Applied Mathematics, Elsevier, 2015, 285, pp.243-255. ⟨10.1016/j.cam.2015.02.030⟩
Publication Year :
2015
Publisher :
Elsevier BV, 2015.

Abstract

International audience; 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.

Details

ISSN :
03770427
Volume :
285
Database :
OpenAIRE
Journal :
Journal of Computational and Applied Mathematics
Accession number :
edsair.doi.dedup.....cfda7d159ead4506eb06fa2a49b05c12
Full Text :
https://doi.org/10.1016/j.cam.2015.02.030