Results 21 to 30 of about 11,086,842 (321)
On approximately convex functions [PDF]
Proceedings of the American Mathematical Society, 1993 The Bernstein-Doetsch theorem on midconvex functions is extended to approximately midconvex functions and to approximately Wright convex functions.
Kazimierz Nikodem, C. T. Ng
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The number of directed k-convex polyominoes [PDF]
, 2015 We present a new method to obtain the generating functions for directed convex polyominoes according to several different statistics including: width, height, size of last column/row and number of corners.
Boussicault, Adrien +2 more
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Subordination by convex functions [PDF]
Proceedings of the American Mathematical Society, 1975 The following theorem is proven: Let F ( z ) F(z) be convex and univalent in Δ = { z : | z | > 1 } , F ( 0 ) = 1 \Delta = \{ z:|z| > 1\} ,F(0)
Stephan Ruscheweyh, D. J. Hallenbeck
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On the (p,h)-convex function and some integral inequalities
, 2014 In this paper, we introduce a new class of (p,h)-convex functions which generalize P-functions and convex, h,p,s-convex, Godunova-Levin functions, and we give some properties of the functions.
Z. Fang, Renjie Shi
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Functions Like Convex Functions [PDF]
Journal of Function Spaces, 2015 The paper deals with convex sets, functions satisfying the global convexity property, and positive linear functionals. Jensen's type inequalities can be obtained by using convex combinations with the common center. Following the idea of the common center, the functional forms of Jensen's inequality are considered in this paper.
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Valuations on Convex Functions [PDF]
International Mathematics Research Notices, 2017 All continuous, SL$(n)$ and translation invariant valuations on the space of convex functions on ${\mathbb R}^n$ are completely classified.
Andrea Colesanti +2 more
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Image Fusion via Sparse Regularization with Non-Convex Penalties
, 2020 The L1 norm regularized least squares method is often used for finding sparse approximate solutions and is widely used in 1-D signal restoration. Basis pursuit denoising (BPD) performs noise reduction in this way.
Achim, Alin +3 more
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An Improved Convergence Analysis for Decentralized Online Stochastic Non-Convex Optimization [PDF]
IEEE Transactions on Signal Processing, 2020 In this paper, we study decentralized online stochastic non-convex optimization over a network of nodes. Integrating a technique called gradient tracking in decentralized stochastic gradient descent, we show that the resulting algorithm, GT-DSGD, enjoys ...
Ran Xin, U. Khan, S. Kar
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An Inequality for Convex Functions
Journal of Mathematical Analysis and Applications, 1994 The authors prove the following interesting inequality for convex functions: Suppose that positive numbers \(s_{i,j}\) \((i= 0,1,2; j= 1,\dots,n)\) satisfy \(s_{1,j}\leq s_{0,j}\leq s_{2,j}\) \((j= 1,\dots,n)\) and \(a_ j s^{-1}_{i,1}+ b_ j s^{-1}_{i,j}= 1\) \((i= 0,1,2; j= 2,\dots,n)\) for positive constants \(a_ j\), \(b_ j\) \((j= 2,\dots,n)\). If \(
Josip Pečarić, Charles E. M. Pearce
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Schur-Convexity of Averages of Convex Functions [PDF]
Journal of Inequalities and Applications, 2011 The object is to give an overview of the study of Schur-convexity of various means and functions and to contribute to the subject with some new results. First, Schur-convexity of the generalized integral and weighted integral quasi-arithmetic mean is studied.
Roqia Ghulam +3 more
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