Results 51 to 60 of about 183,031 (208)
On Strongly Convex Functions [PDF]
, 2014 The main results of this paper give a connection between strong Jensen convexity and strong convexity type inequalities. We are also looking for the optimal Takagi type function of strong convexity.
Házy, Attila, Makó, Judit
core
ON THE NEIGHBOURHOODS OF STRONGLY CONVEX FUNCTIONS
Tamkang Journal of Mathematics, 1996 In this paper neighbourhoods of strongly convex and strongly starlike function are determined.
Parvatham, R., Premabai, Millicent
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Journal of Inequalities and Applications, 2023 In this paper, we investigate the properties of a newly introduced class of functions, strongly reciprocally (p, h)-convex functions of higher order. We establish Hermite–Hadamard-type and Fejér-type inequalities for this class of functions. Additionally,
Han Li +3 more
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, 2018 This paper considers a conceptual version of a convex optimization algorithm whic is based on replacing a convex optimization problem with the root-finding problem for the approximate sub-differential mapping which is solved by repeated projection onto ...
Nurminski, Evgeni
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Generalized Hadamard Fractional Integral Inequalities for Strongly
, 2021 Chao Miao +3 more
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Adaptive Restart of the Optimized Gradient Method for Convex Optimization
, 2017 First-order methods with momentum such as Nesterov's fast gradient method are very useful for convex optimization problems, but can exhibit undesirable oscillations yielding slow convergence rates for some applications.
Fessler, Jeffrey A., Kim, Donghwan
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Non-ergodic Convergence Analysis of Heavy-Ball Algorithms
, 2018 In this paper, we revisit the convergence of the Heavy-ball method, and present improved convergence complexity results in the convex setting. We provide the first non-ergodic O(1/k) rate result of the Heavy-ball algorithm with constant step size for ...
Guan, Lei +5 more
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Some Hermite-Hadamard inequalities for strongly harmonic convex set-valued functions [PDF]
, 2022 Gabriel Santana, Maira Valera
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An Accelerated Proximal Coordinate Gradient Method and its Application to Regularized Empirical Risk Minimization [PDF]
, 2014 We consider the problem of minimizing the sum of two convex functions: one is smooth and given by a gradient oracle, and the other is separable over blocks of coordinates and has a simple known structure over each block.
Lin, Qihang, Lu, Zhaosong, Xiao, Lin
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On Generalized Strongly p-Convex Functions of Higher Order
Journal of Mathematics, 2020 The aim of this paper is to introduce the definition of a generalized strongly p-convex function for higher order. We will develop some basic results related to generalized strongly p-convex function of higher order.
Muhammad Shoaib Saleem +4 more
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