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Titlebook: Geometric Science of Information; Second International Frank Nielsen,Frédéric Barbaresco Conference proceedings 2015 Springer International

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楼主: patch-test
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Affine-Invariant Riemannian Distance Between Infinite-Dimensional Covariance Operatorse. This is the generalization of the Riemannian manifold of symmetric, positive definite matrices to the infinite-dimensional setting. In particular, in the case of covariance operators in a Reproducing Kernel Hilbert Space (RKHS), we provide a closed form solution, expressed via the corresponding Gram matrices.
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A Sub-Riemannian Modular Approach for Diffeomorphic Deformationsribe transformations. The method, built on a coherent sub-Riemannian framework, defines a metric on modular deformations and characterises optimal deformations as geodesics for this metric. We will present a generic way to build local affine transformations as deformation modules, and display examples.
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Optimal Transport, Independance Versus Indetermination Duality, Impact on a New Copula Designction with the MKP transportation problem (MKP, stands for Monge-Kantorovich Problem). Using the duality between “independance” and “indetermination” structures, shown in this former paper, we are in a position to derive a novel approach to design a copula, suitable and efficient for anomaly detection in IT systems analysis.
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Barycenter in Wasserstein Spaces: Existence and Consistency on . as its Fréchet mean. The paper establishes its existence and states consistency with respect to .. We thus extends previous results on ., with conditions on . or on the sequence converging to . for consistency.
发表于 2025-3-24 11:36:10 | 显示全部楼层
https://doi.org/10.1007/978-3-319-25040-3Bayesian statistics; Optimal transport; Optimization on manifolds; Stochastic geometry; Topological info
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