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Sharp Bounds by the Generalized Logarithmic Mean for the Geometric Weighted Mean of the Geometric and Harmonic Means [PDF]
Journal of Applied Mathematics, 2012 We present sharp upper and lower generalized logarithmic mean bounds for the geometric weighted mean of the geometric and harmonic means.
Wei-Mao Qian, Bo-Yong Long
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Extensions to Mean–Geometric Mean Linking
MathematicsMean-geometric mean (MGM) linking is a widely used method for linking two groups within the two-parameter logistic (2PL) item response model. However, the presence of differential item functioning (DIF) can lead to biased parameter estimates using the ...
Alexander Robitzsch
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Optimal two-parameter geometric and arithmetic mean bounds for the Sándor–Yang mean
Journal of Inequalities and Applications, 2019 In the article, we provide the sharp bounds for the Sándor–Yang mean in terms of certain families of the two-parameter geometric and arithmetic mean and the one-parameter geometric and harmonic means.
Wei-Mao Qian +3 more
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Sharp Geometric Mean Bounds for Neuman Means [PDF]
Abstract and Applied Analysis, 2014 We find the best possible constants α1,α2,β1,β2∈[0,1/2] and α3,α4,β3,β4∈[1/2,1] such that the double inequalities G(α1a+(1-α1)b,α1b + (1-α1)a)
Yan Zhang, Yu-Ming Chu, Yun-Liang Jiang
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Kernel Geometric Mean Metric Learning
Applied Sciences, 2023 Geometric mean metric learning (GMML) algorithm is a novel metric learning approach proposed recently. It has many advantages such as unconstrained convex objective function, closed form solution, faster computational speed, and interpretability over ...
Zixin Feng +4 more
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Two Sharp Inequalities for Power Mean, Geometric Mean, and Harmonic Mean
Journal of Inequalities and Applications, 2009 For p∈R, the power mean of order p of two positive numbers a and b is defined by Mp(a,b)=((ap+bp)/2)1/p,p≠0, and Mp(a,b)=ab, p=0.
Wei-Feng Xia, Yu-Ming Chu
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Mean Estimation on the Diagonal of Product Manifolds
Algorithms, 2022 Computing sample means on Riemannian manifolds is typically computationally costly, as exemplified by computation of the Fréchet mean, which often requires finding minimizing geodesics to each data point for each step of an iterative optimization scheme.
Mathias Højgaard Jensen, Stefan Sommer
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Joint Access Configuration and Beamforming for Cell-Free Massive MIMO Systems With Dynamic TDD
IEEE Access, 2022 We address the trade-off between system throughput and user equipment (UE) fairness in dynamic time division duplex (TDD) cell-free (CF)-massive multiple-input multiple-output (mMIMO) systems, developing to that end a joint access point (AP) access ...
Shuto Fukue +3 more
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The Multi-Objective Transportation Problem Solve with Geometric Mean and Penalty Methods
Indonesian Journal of Innovation and Applied Sciences, 2023 The traditional (classical) Transportation Problem (TP) can be viewed as a specific case of the Linear Programming (LP) problem, as well as its models are used to find the best solution for the problem of predetermined how many units of a good or service
K.P.O.Niluminda, E.M.U.S.B.Ekanayake
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On the Geometric Mean Operator
Journal of Mathematical Analysis and Applications, 1994 The authors give a characterization of pairs of weights \((u,v)\) such that the geometric mean operator \(Gf(x)= \exp((1/x) \int_ 0^ x \log f(t) dt)\), defined for \(f>0\) almost everywhere on \((0,\infty)\), is bounded from \(L_{p,v} (0,\infty)\) to \(L_{q,u} (0,\infty)\), where \(01\) the good weights for \(G\) coincide with those good for the ...
Pick, L., Opic, B.
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