Zobrazeno 1 - 10
of 319
pro vyhledávání: '"Clémençon Stéphan"'
It is the purpose of this paper to investigate the issue of estimating the regularity index $\beta>0$ of a discrete heavy-tailed r.v. $S$, \textit{i.e.} a r.v. $S$ valued in $\mathbb{N}^*$ such that $\mathbb{P}(S>n)=L(n)\cdot n^{-\beta}$ for all $n\g
Externí odkaz:
http://arxiv.org/abs/2407.05281
Autor:
Fernández, Carlos, Clémençon, Stephan
The main purpose of this article to extend the notion of statistical depth to the case of sample paths of a Markov chain. Initially introduced to define a center-outward ordering of points in the support of a multivariate distribution, depth function
Externí odkaz:
http://arxiv.org/abs/2406.16759
Many modern spatio-temporal data sets, in sociology, epidemiology or seismology, for example, exhibit self-exciting characteristics, triggering and clustering behaviors both at the same time, that a suitable Hawkes space-time process can accurately c
Externí odkaz:
http://arxiv.org/abs/2406.06849
Autor:
Limnios, Myrto, Clémençon, Stéphan
In this paper we develop a novel nonparametric framework to test the independence of two random variables $\mathbf{X}$ and $\mathbf{Y}$ with unknown respective marginals $H(dx)$ and $G(dy)$ and joint distribution $F(dx dy)$, based on {\it Receiver Op
Externí odkaz:
http://arxiv.org/abs/2403.07464
Motivated by the increasing availability of data of functional nature, we develop a general probabilistic and statistical framework for extremes of regularly varying random elements $X$ in $L^2[0,1]$. We place ourselves in a Peaks-Over-Threshold fram
Externí odkaz:
http://arxiv.org/abs/2308.01023
The evaluation of natural language processing (NLP) systems is crucial for advancing the field, but current benchmarking approaches often assume that all systems have scores available for all tasks, which is not always practical. In reality, several
Externí odkaz:
http://arxiv.org/abs/2305.10284
As the issue of robustness in AI systems becomes vital, statistical learning techniques that are reliable even in presence of partly contaminated data have to be developed. Preference data, in the form of (complete) rankings in the simplest situation
Externí odkaz:
http://arxiv.org/abs/2303.12878
The statistical learning problem consists in building a predictive function $\hat{f}$ based on independent copies of $(X,Y)$ so that $Y$ is approximated by $\hat{f}(X)$ with minimum (squared) error. Motivated by various applications, special attentio
Externí odkaz:
http://arxiv.org/abs/2303.03084
The two-sample problem, which consists in testing whether independent samples on $\mathbb{R}^d$ are drawn from the same (unknown) distribution, finds applications in many areas. Its study in high-dimension is the subject of much attention, especially
Externí odkaz:
http://arxiv.org/abs/2302.03592
Autor:
Conti, Jean-Rémy, Clémençon, Stéphan
The ROC curve is the major tool for assessing not only the performance but also the fairness properties of a similarity scoring function. In order to draw reliable conclusions based on empirical ROC analysis, accurately evaluating the uncertainty lev
Externí odkaz:
http://arxiv.org/abs/2211.07245