3 papers
stat.ME2025
Clustering Tails in High Dimension
Liujun Chen, Marco Oesting, Chen Zhou
One potential solution to combat the scarcity of tail observations in extreme value analysis is to integrate information from multiple datasets sharing similar tail properties, for…
stat.ME2025
Evaluation of binary classifiers for asymptotically dependent and independent extremes
Juliette Legrand, Philippe Naveau, Marco Oesting
Machine learning classification methods usually assume that all possible classes are sufficiently present within the training set. Due to their inherent rarities, extreme events ar…
stat.ME2024
Extremes in High Dimensions: Methods and Scalable Algorithms
Johannes Lederer, Marco Oesting
Extreme value theory for univariate and low-dimensional observations has been explored in considerable detail, but the field is still in an early stage regarding high-dimensional s…