In this paper we estimate the sparse dependence structure in the tail re...
In smart transportation, intelligent systems avoid potential collisions ...
Humans exhibit disagreement during data labeling. We term this disagreem...
An important problem in extreme-value theory is the estimation of the
pr...
Extreme U-statistics arise when the kernel of a U-statistic has a high d...
The global financial crisis of 2007-2009 highlighted the crucial role
sy...
The distributed Hill estimator is a divide-and-conquer algorithm for
est...
The availability of massive datasets allows for conducting extreme value...
We consider the problem of dimensionality reduction for prediction of a
...
The block maxima (BM) approach in extreme value analysis fits a sample o...
Although deep learning has achieved remarkable successes over the past y...
Few-shot Learning (FSL) which aims to learn from few labeled training da...
The statistical theory of extremes is extended to observations that are
...
Single image inverse problem is a notoriously challenging ill-posed prob...
Classical extreme value statistics consists of two fundamental approache...
Safety is paramount for mobile robotic platforms such as self-driving ca...