Introduces a penalized least squares estimator with pseudo-norm penalization for parametric extreme-value mixture models and a data-driven algorithm to identify extreme directions.
Extremes of structural causal models
3 Pith papers cite this work. Polarity classification is still indexing.
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Formalizes causal pathways of rare events and conditions for their abstraction from full causal graphs in structural equation models.
A survey of recent methods that apply extreme value theory to enable extrapolation in statistical learning and machine learning.
citing papers explorer
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A penalized least squares estimator for extreme-value mixture models
Introduces a penalized least squares estimator with pseudo-norm penalization for parametric extreme-value mixture models and a data-driven algorithm to identify extreme directions.
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Formalizing and falsifying causal pathways of rare events
Formalizes causal pathways of rare events and conditions for their abstraction from full causal graphs in structural equation models.
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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.