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Proximal operator of quotient functions with application to a feasibility problem in query optimization
- 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.
- Subjects :
- Discrete mathematics
Shrinkage function
Applied Mathematics
Regular polygon
Of the form
010103 numerical & computational mathematics
02 engineering and technology
First order
Query optimization
01 natural sciences
Combinatorics
Computational Mathematics
Norm (mathematics)
0202 electrical engineering, electronic engineering, information engineering
020201 artificial intelligence & image processing
[MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC]
0101 mathematics
Reciprocal
Quotient
Mathematics
Subjects
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