Proves that transformed paths of heavy-tailed extremal processes and random walks in growing dimensions converge in distribution to Poisson cluster processes, implying Gromov-Hausdorff convergence of the paths as metric spaces and convergence in counting measure spaces.
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A survey of recent methods that apply extreme value theory to enable extrapolation in statistical learning and machine learning.
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Ranges of Extremal Processes and Heavy-Tailed Random Walks in Spaces of Growing Dimension
Proves that transformed paths of heavy-tailed extremal processes and random walks in growing dimensions converge in distribution to Poisson cluster processes, implying Gromov-Hausdorff convergence of the paths as metric spaces and convergence in counting measure spaces.
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Extrapolation in Statistical Learning with Extreme Value Theory
A survey of recent methods that apply extreme value theory to enable extrapolation in statistical learning and machine learning.