Results 1 to 10 of about 1,694,937 (192)
Regularly ideal invariant convergence of double sequences
Journal of Inequalities and Applications, 2021 In this paper, we introduce the notions of regularly invariant convergence, regularly strongly invariant convergence, regularly p-strongly invariant convergence, regularly ( I σ , I 2 σ ) $(\mathcal{I}_{\sigma },\mathcal{I}^{\sigma }_{2})$ -convergence ...
Nimet Pancaroǧlu Akın
doaj +3 more sources
Lacunary I-invariant convergence
Cumhuriyet Science Journal, 2020 In this study, firstly, we introduce the notion of lacunary invariant uniform density of any subset E of the set N (the set of all natural numbers). Then, as associated with this notion, we give the definition of lacunary I_σ-convergence for
Fatih Nuray, Uğur Ulusu
doaj +4 more sources
Lacunary I_2-Invariant Convergence and Some Properties
International Journal of Analysis and Applications, 2018 In this paper, the concept of lacunary invariant uniform density of any subset $A$ of the set $\mathbb{N}\times\mathbb{N}$ is defined. Associate with this, the concept of lacunary $\mathcal{I}_2$-invariant convergence for double sequences is given. Also,
Ugur Ulusu, Erdinc Dundar, Fatih Nuray
doaj +9 more sources
Affine Invariant Convergence Rates of the Conditional Gradient Method [PDF]
SIAM Journal on Optimization, 2021 We show that the conditional gradient method for the convex composite problem \[\min_x\{f(x) + \Psi(x)\}\] generates primal and dual iterates with a duality gap converging to zero provided a suitable {\em growth property} holds and the algorithm makes a ...
Javier F. Peña
semanticscholar +4 more sources
Wijsman quasi-invariant convergence [PDF]
Creative Mathematics and Informatics, 2019 In this study, we defined concepts of Wijsman quasi-invariant convergence, Wijsman quasi-strongly invariant convergence and Wijsman quasi-strongly q-invariant convergence.
Esra Gulle, Uǧur Ulusu
semanticscholar +4 more sources
On the invariant mean and statistical convergence
Applied Mathematics Letters, 2009 The authors introduce two kinds of summability methods, \(\sigma\)-statistical summability and statistical \(\sigma\)-summability, by using the concepts of invariant means, and statistical convergence. A sequence \((x_{k})\) is said to be \(\sigma\)-statistically convergent to \(L\) if for every \( \varepsilon> 0\) \[ \lim_{p\rightarrow\infty}\frac{1 ...
M Mursaleen
exaly +3 more sources
Accelerated affine-invariant convergence rates of the Frank–Wolfe algorithm with open-loop step-sizes [PDF]
Mathematical programming, 2023 Recent papers have shown that the Frank–Wolfe algorithm (FW) with open-loop step-sizes exhibits rates of convergence faster than the iconic O(t-1)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage ...
E. Wirth, Javier Peña, S. Pokutta
semanticscholar +1 more source
On Convergence of FedProx: Local Dissimilarity Invariant Bounds, Non-smoothness and Beyond [PDF]
Neural Information Processing Systems, 2022 The FedProx algorithm is a simple yet powerful distributed proximal point optimization method widely used for federated learning (FL) over heterogeneous data.
Xiao-Tong Yuan, P. Li
semanticscholar +1 more source
Some New Types of Convergence Definitions for Random Variable Sequences
International Journal of Analysis and Applications, 2022 In this paper, we introduce the concepts of invariant convergence in probability, statistically invariant convergence in probability, invariant convergence almost surely, invariant convergence in distribution and invariant convergence in Lp-norm for ...
Saadettin Aydın
doaj +1 more source
Convergence of Invariant Graph Networks
CoRR, 2022 Although theoretical properties such as expressive power and over-smoothing of graph neural networks (GNN) have been extensively studied recently, its convergence property is a relatively new direction. In this paper, we investigate the convergence of one powerful GNN, Invariant Graph Network (IGN) over graphs sampled from graphons.
Chen Cai, Yusu Wang 0001
openaire +3 more sources