New estimates on generalized Hermite–Hadamard–Mercer-type inequalities
The concept of a convex function plays a crucial role in fields of mathematical analysis and inequality theory. The importance of convex functions is exemplified by Mercer’s inequality.
Çetin Yıldız +4 more
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A version of Hermite-Hadamard-Mercer inequality and associated results
Over the past decade, the Hermite-Hadamard inequality has attracted significant attention from mathematicians, leading to the development of various extensions and generalizations involving different fractional operators, stochastic processes ...
Zhenglin Zhang +5 more
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Examining privilege and power in US urban parks and open space during the double crises of antiblack racism and COVID-19. [PDF]
Hoover FA, Lim TC.
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The effects of IMF loan conditions on poverty in the developing world. [PDF]
Biglaiser G, McGauvran RJ.
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Refining Jensen–Mercer inequality and its applications in probability and statistics
This paper focuses on refining the Jensen–Mercer inequality and extending its applications to various important inequalities, including Hölder’s, Ky Fan, and AM-GM inequalities.
Rabia Bibi, Sajid Ali
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New Results on Majorized Discrete Jensen–Mercer Inequality for Raina Fractional Operators
As the most important inequality, the Hermite–Hadamard–Mercer inequality has attracted the interest of numerous additional mathematicians. Numerous findings on this inequality have been developed in recent years.
Çetin Yildiz +2 more
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Proceedings of the 17TH International Congress on Circumpolar Health, August 12-15, 2018, Copenhagen, Denmark (ICCH17). [PDF]
Koch A.
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This study generalizes Hermite–Hadamard–Mercer type inequalities using Riemann–Liouville fractional integrals within the framework of multiplicative calculus.
Abdul Mateen +3 more
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Some Generalizations of Mercer inequality and its operator extensions
We study the Mercer inequality and its operator extension for superquadratic functions. In particular, we give a more general form of the Mercer inequality by replacing some constants by positive operators.
Kian, Mohsen, Mazraj, Zainab Peymani
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Multi-class SVMs: From Tighter Data-Dependent Generalization Bounds to Novel Algorithms
This paper studies the generalization performance of multi-class classification algorithms, for which we obtain, for the first time, a data-dependent generalization error bound with a logarithmic dependence on the class size, substantially improving the ...
Binder, Alexander +3 more
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