European Journal of Applied MathematicsThe unprecedented success of deep learning (DL) makes it unchallenged when it comes to classification problems. However, it is well established that the current DL methodology produces universally unstable neural networks (NNs).
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Optimization applications of Goldbach's conjecture. [PDF]
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Enforcing Dirichlet boundary conditions in physics-informed neural networks and variational physics-informed neural networks. [PDF]
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A Simplified Convex Optimization Model for Image Restoration with Multiplicative Noise. [PDF]
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A fast continuous time approach with time scaling for nonsmooth convex optimization. [PDF]
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Time Rescaling of a Primal-Dual Dynamical System with Asymptotically Vanishing Damping. [PDF]
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On the asymptotic behavior of the Douglas-Rachford and proximal-point algorithms for convex optimization. [PDF]
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Modeling Covid-19 incidence by the renewal equation after removal of administrative bias and noise [PDF]
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Homogenisation of dynamical optimal transport on periodic graphs. [PDF]
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Equivalent Formulations of Optimal Control Problems with Maximum Cost and Applications. [PDF]
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