13 citations · 48 across the 23 of their papers we have counts for
28 papers
Principal Component Analysis for Multivariate Extremes
Dan Cooley, Anne Sabourin, Troy Wixson
This chapter explores ways to reduce the dimensionality of the data while preserving key information relevant to the analysis of multivariate extreme values.
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…
Out-of-Distribution generalization of quantile regression with heavy tailed inputs: an SVM approach
Baptiste Leroux, Clément Dombry, Anne Sabourin
We study quantile regression in an extrapolation regime where the covariate takes unusually large values. Under regular variation assumptions, extreme observations can be effective…
Zero-couplings of infinite measures with cyclically monotone support and multivariate regular variation
Alexandre Reber, Anne Sabourin, Johan Segers +1
We study cyclically monotone transport plans between measures in , the class of Borel measures on that are finite on sets…
Extrapolation in Statistical Learning with Extreme Value Theory
Sebastian Engelke, Nicola Gnecco, Anne Sabourin
Extreme value theory provides rigorous theory and statistical tools for extrapolation in machine learning, particularly in settings where traditional methods struggle due to data s…
Adaptive tail index estimation: minimal assumptions and non-asymptotic guarantees
Johannes Lederer, Anne Sabourin, Mahsa Taheri
A notoriously difficult challenge in extreme value theory is the choice of the number , where is the total sample size, of extreme data points to consider for inference…
Multi-site modelling and reconstruction of past extreme skew surges along the French Atlantic coast
Nathan Huet, Philippe Naveau, Anne Sabourin
Appropriate modelling of extreme skew surges is crucial, particularly for coastal risk management. Our study focuses on modelling extreme skew surges along the French Atlantic coas…
Weak Signals and Heavy Tails: Learning Theory meets Extreme Value Analysis
Stephan Clémençon, Anne Sabourin
The masses of data now available have opened up the prospect of discovering weak signals using machine-learning algorithms, with a view to predictive or interpretation tasks. As th…
Sharp error bounds for imbalanced classification: how many examples in the minority class?
Anass Aghbalou, François Portier, Anne Sabourin
When dealing with imbalanced classification data, reweighting the loss function is a standard procedure allowing to equilibrate between the true positive and true negative rates wi…
Regular Variation in Hilbert Spaces and Principal Component Analysis for Functional Extremes
Stephan Clémençon, Nathan Huet, Anne Sabourin
Motivated by the increasing availability of data of functional nature, we develop a general probabilistic and statistical framework for extremes of regularly varying random element…
On Regression in Extreme Regions
Stephan Clémençon, Nathan Huet, Anne Sabourin
We establish a statistical learning theoretical framework aimed at extrapolation, or out-of-domain generalization, on the unobserved tails of covariates in continuous regression pr…
On the bias of K-fold cross validation with stable learners
Anass Aghbalou, François Portier, Anne Sabourin
This paper investigates the efficiency of the K-fold cross-validation (CV) procedure and a debiased version thereof as a means of estimating the generalization risk of a learning a…
Cross-validation on Extreme Regions
Anass Aghbalou, Patrice Bertail, François Portier +1
We conduct a non asymptotic study of the Cross Validation (CV) estimate of the generalization risk for learning algorithms dedicated to extreme regions of the covariates space. In…
Uniform concentration bounds for frequencies of rare events
Stéphane Lhaut, Anne Sabourin, Johan Segers
New Vapnik and Chervonenkis type concentration inequalities are derived for the empirical distribution of an independent random sample. Focus is on the maximal deviation over class…
Tail inverse regression for dimension reduction with extreme response
Anass Aghbalou, François Portier, Anne Sabourin +1
We consider the problem of supervised dimension reduction with a particular focus on extreme values of the target to be explained by a covariate vector $X \in \mat…
Concentration bounds for the empirical angular measure with statistical learning applications
Stéphan Clémençon, Hamid Jalalzai, Stéphane Lhaut +2
The angular measure on the unit sphere characterizes the first-order dependence structure of the components of a random vector in extreme regions and is defined in terms of standar…
Heavy-tailed Representations, Text Polarity Classification & Data Augmentation
Hamid Jalalzai, Pierre Colombo, Chloé Clavel +4
The dominant approaches to text representation in natural language rely on learning embeddings on massive corpora which have convenient properties such as compositionality and dist…
A Multivariate Extreme Value Theory Approach to Anomaly Clustering and Visualization
Maël Chiapino, Stéphan Clémençon, Vincent Feuillard +1
In a wide variety of situations, anomalies in the behaviour of a complex system, whose health is monitored through the observation of a random vector X = (X1,. .. , X d) valued in…
Principal Component Analysis for Multivariate Extremes
Holger Drees, Anne Sabourin
The first order behavior of multivariate heavy-tailed random vectors above large radial thresholds is ruled by a limit measure in a regular variation framework. For a high dimensio…
Identifying groups of variables with the potential of being large simultaneously
Maël Chiapino, Anne Sabourin, Johan Segers
Identifying groups of variables that may be large simultaneously amounts to finding out which joint tail dependence coefficients of a multivariate distribution are positive. The as…
Max K-armed bandit: On the ExtremeHunter algorithm and beyond
Mastane Achab, Stephan Clémençon, Aurélien Garivier +2
This paper is devoted to the study of the max K-armed bandit problem, which consists in sequentially allocating resources in order to detect extreme values. Our contribution is two…
Sparse Representation of Multivariate Extremes with Applications to Anomaly Ranking
Nicolas Goix, Anne Sabourin, Stéphan Clémençon
Extremes play a special role in Anomaly Detection. Beyond inference and simulation purposes, probabilistic tools borrowed from Extreme Value Theory (EVT), such as the angular measu…
Marginal standardization of upper semicontinuous processes. with application to max-stable processes
Anne Sabourin, Johan Segers
Extreme-value theory for random vectors and stochastic processes with continuous trajectories is usually formulated for random objects all of whose univariate marginal distribution…
Sparsity in Multivariate Extremes with Applications to Anomaly Detection
Nicolas Goix, Anne Sabourin, Stéphan Clémençon
Capturing the dependence structure of multivariate extreme events is a major concern in many fields involving the management of risks stemming from multiple sources, e.g. portfolio…