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math.ST2026
Polar Depth for Potentially Heavy-Tailed Data
Stephan Clemençon, Carlos Fernándes, Pavlo Mozharovskyi +1
Motivated by the analysis of the behaviour of extremes from multivariate heavy-tailed distributions, we introduce a novel notion of statistical depth, referred to as Polar Depth. T…
math.ST2006★ 80 cited
Ranking the best instances
Stéphan Clémençon, Nicolas Vayatis
We formulate the local ranking problem in the framework of bipartite ranking where the goal is to focus on the best instances. We propose a methodology based on the construction of…