Lacunary ℐ-Invariant Convergence of Sequence of Sets in Intuitionistic Fuzzy Metric Spaces
Journal of Mathematics, 2021 The concepts of invariant convergence, invariant statistical convergence, lacunary invariant convergence, and lacunary invariant statistical convergence for set sequences were introduced by Pancaroğlu and Nuray (2013).
Mualla Birgül Huban
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Disentangled Federated Learning for Tackling Attributes Skew via Invariant Aggregation and Diversity Transferring [PDF]
International Conference on Machine Learning, 2022 Attributes skew hinders the current federated learning (FL) frameworks from consistent optimization directions among the clients, which inevitably leads to performance reduction and unstable convergence.
Zhengquan Luo +4 more
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Machines, 2021 For mechanical compound fault, it is of great significance to employ the vibration signal of a single-channel compound fault to analyze and realize the separation of multiple fault sources, which is essentially the problem of single-channel blind source ...
Haodong Yuan, Nailong Wu, Xinyuan Chen
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The backward Euler-Maruyama method for invariant measures of stochastic differential equations with super-linear coefficients [PDF]
Applied Numerical Mathematics, 2022 The backward Euler-Maruyama (BEM) method is employed to approximate the invariant measure of stochastic differential equations, where both the drift and the diffusion coefficient are allowed to grow super-linearly.
W. Liu, X. Mao, Yuehui Wu
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Global Convergence of Policy Gradient Primal–Dual Methods for Risk-Constrained LQRs [PDF]
IEEE Transactions on Automatic Control, 2021 While the techniques in optimal control theory are often model-based, the policy optimization (PO) approach directly optimizes the performance metric of interest. Even though it has been an essential approach for reinforcement learning problems, there is
Feiran Zhao, Keyou You, T. Başar
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Empirical approximation to invariant measures for McKean–Vlasov processes: Mean-field interaction vs self-interaction [PDF]
Bernoulli, 2021 This paper proves that, under a monotonicity condition, the invariant probability measure of a McKean--Vlasov process can be approximated by weighted empirical measures of some processes including itself.
Kai Du, Yifan Jiang, Jinfeng Li
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Convergence Groups are not Invariably Generated [PDF]
International Mathematics Research Notices, 2014 It was conjectured in [KLS14] that non-elementary word hyperbolic groups are never invariably generated. We show that this is indeed the case even for the much larger class of convergence groups.
openaire +2 more sources
A New Newton Method with Memory for Solving Nonlinear Equations
Mathematics, 2020 A new Newton method with memory is proposed by using a variable self-accelerating parameter. Firstly, a modified Newton method without memory with invariant parameter is constructed for solving nonlinear equations. Substituting the invariant parameter of
Xiaofeng Wang, Yuxi Tao
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Learning Invariant Representation for Unsupervised Image Restoration [PDF]
Computer Vision and Pattern Recognition, 2020 Recently, cross domain transfer has been applied for unsupervised image restoration tasks. However, directly applying existing frameworks would lead to domain-shift problems in translated images due to lack of effective supervision.
Wenchao Du, Hu Chen, Hongyu Yang
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Lupaş post quantum Bernstein operators over arbitrary compact intervals
Karpatsʹkì Matematičnì Publìkacìï, 2021 This paper deals with Lupaş post quantum Bernstein operators over arbitrary closed and bounded interval constructed with the help of Lupaş post quantum Bernstein bases.
A. Khan +3 more
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