Results 71 to 80 of about 1,415,554 (169)
Converting Level Set Gradients to Shape Gradients [PDF]
, 2010 The level set representation of shapes is useful for shape evolution and is widely used for the minimization of energies with respect to shapes. Many algorithms consider energies depending explicitly on the signed distance function (SDF) associated with a shape, and differentiate these energies with respect to the SDF directly in order to make the ...
Chen, Siqi +2 more
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Response: Alternative approaches for systematic review
Global Epidemiology, 2022 Julie E. Goodman +2 more
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The Adjoint Method Formulation for an Inverse Problem in the Generalized Black-Scholes Model [PDF]
Journal of Systemics, Cybernetics and Informatics, 2006 A general framework is developed to treat optimal control problems for a generalized Black-Scholes model, which is used for option pricing. The volatility function is retrieved from a set of market observations.
PIERRE NGNEPIEBA
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Supervised Brain Tumor Segmentation Based on Gradient and Context-Sensitive Features
Frontiers in Neuroscience, 2019 Gliomas have the highest mortality rate and prevalence among the primary brain tumors. In this study, we proposed a supervised brain tumor segmentation method which detects diverse tumoral structures of both high grade gliomas and low grade gliomas in ...
Junting Zhao +6 more
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, 2018 For a locally Lipschitz continuous function $f:X\to\mathbb{R}$ the generalized gradient $\partial f(x)$ of Clarke is used to develop some (set-valued) gradient on a set $A\subset X$. Existence, uniqueness and some approximation are considered for optimal descent directions on set $A$.
Mankau, Jan, Schuricht, Friedemann
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Nonlinear Sherman-type inequalities
Advances in Nonlinear Analysis, 2018 An important class of Schur-convex functions is generated by convex functions via the well-known Hardy–Littlewood–Pólya–Karamata inequality. Sherman’s inequality is a natural generalization of the HLPK inequality.
Niezgoda Marek
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CoRR, 2019 The goal of policy gradient approaches is to find a policy in a given class of policies which maximizes the expected return. Given a differentiable model of the policy, we want to apply a gradient-ascent technique to reach a local optimum. We mainly use gradient ascent, because it is theoretically well researched.
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Journal of Functional Analysis, 2000 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Advanced ScienceAn efficient method for the synthesis of a self‐supporting carbon framework (denoted Gra‐GC‐MoSe2) is proposed with a triple‐gradient structure—in sodiophilic sites, pore volume, and electrical conductivity—which facilitates the highly efficient ...
Weishan Cao +8 more
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