Proximal methods for point source localisation [PDF]
Journal of Nonsmooth Analysis and Optimization, 2023 Point source localisation is generally modelled as a Lasso-type problem on measures. However, optimisation methods in non-Hilbert spaces, such as the space of Radon measures, are much less developed than in Hilbert spaces.
Tuomo Valkonen
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Convergence aspects for sets of measures with divergences and boundary conditions [PDF]
Journal of Mathematical Analysis and Applications, 2023 In this paper we study set convergence aspects for Banach spaces of vector-valued measures with divergences (represented by measures or by functions) and applications. We consider a form of normal trace characterization to establish subspaces of measures
Nicholas G. Chisholm +1 more
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Linear convergence of accelerated conditional gradient algorithms in spaces of measures [PDF]
E S A I M: Control, Optimisation and Calculus of Variations, 2019 A class of generalized conditional gradient algorithms for the solution of optimization problem in spaces of Radon measures is presented. The method iteratively inserts additional Dirac-delta functions and optimizes the corresponding coefficients.
Konstantin Pieper, Daniel Walter
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Rearrangement and Convergence in Spaces of Measurable Functions [PDF]
Journal of Inequalities and Applications, 2007 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
CAPONETTI, Diana +2 more
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Smart working is not so smart: Always-on lives and the dark side of platformisation
Work Organisation, Labour and Globalisation, 2021 This article investigates the lived experiences of remote workers during the Italian lockdown, and the role of digital platforms in their working and everyday life activities, as well as the consequences of home confinement
Elisabetta Risi, Riccardo Pronzato
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Convergence and concentration of empirical measures under Wasserstein distance in unbounded functional spaces [PDF]
Bernoulli, 2018 We provide upper bounds of the expected Wasserstein distance between a probability measure and its empirical version, generalizing recent results for finite dimensional Euclidean spaces and bounded functional spaces.
Jing Lei
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Sharp asymptotic and finite-sample rates of convergence of empirical measures in Wasserstein distance [PDF]
Bernoulli, 2017 The Wasserstein distance between two probability measures on a metric space is a measure of closeness with applications in statistics, probability, and machine learning.
J. Weed, F. Bach
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Computing the Gromov-Wasserstein Distance between Two Surface Meshes Using Optimal Transport
Algorithms, 2023 The Gromov-Wasserstein (GW) formalism can be seen as a generalization of the optimal transport (OT) formalism for comparing two distributions associated with different metric spaces.
Patrice Koehl +2 more
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On Null-Continuity of Monotone Measures
Mathematics, 2020 The null-continuity of monotone measures is a weaker condition than continuity from below and possesses many special properties. This paper further studies this structure characteristic of monotone measures.
Jun Li
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Bayesian inference of a non-local proliferation model
Royal Society Open Science, 2021 From a systems biology perspective, the majority of cancer models, although interesting and providing a qualitative explanation of some problems, have a major disadvantage in that they usually miss a genuine connection with experimental data. Having this
Zuzanna Szymańska +3 more
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