Search Results for author: Anne Sabourin

Found 13 papers, 1 papers with code

Sharp error bounds for imbalanced classification: how many examples in the minority class?

no code implementations23 Oct 2023 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 within the risk measure.

imbalanced classification

Regular Variation in Hilbert Spaces and Principal Component Analysis for Functional Extremes

no code implementations2 Aug 2023 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 elements $X$ in $L^2[0, 1]$.

Dimensionality Reduction

On Regression in Extreme Regions

no code implementations6 Mar 2023 Nathan Huet, Stephan Clémençon, Anne Sabourin

It is then shown that an asymptotic notion of risk can be tailored to summarize appropriately predictive performance in extreme regions of the input space.

regression

Concentration bounds for the empirical angular measure with statistical learning applications

no code implementations7 Apr 2021 Stéphan Clémençon, Hamid Jalalzai, Stéphane Lhaut, Anne Sabourin, Johan Segers

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 standardized margins.

Binary Classification Unsupervised Anomaly Detection +1

Heavy-tailed Representations, Text Polarity Classification & Data Augmentation

no code implementations NeurIPS 2020 Hamid Jalalzai, Pierre Colombo, Chloé Clavel, Eric Gaussier, Giovanna Varni, Emmanuel Vignon, Anne Sabourin

The dominant approaches to text representation in natural language rely on learning embeddings on massive corpora which have convenient properties such as compositionality and distance preservation.

Attribute Data Augmentation +4

Regularly varying representation for sentence embedding

no code implementations25 Sep 2019 Hamid Jalalzai, Pierre Colombo, Chloé Clavel, Eric Gaussier, Giovanna Varni, Emmanuel Vignon, Anne Sabourin

The dominant approaches to sentence representation in natural language rely on learning embeddings on massive corpuses.

Attribute Sentence +3

A Multivariate Extreme Value Theory Approach to Anomaly Clustering and Visualization

1 code implementation17 Jul 2019 Maël Chiapino, Stéphan Clémençon, Vincent Feuillard, Anne Sabourin

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,.

Clustering Graph Mining

Principal Component Analysis for Multivariate Extremes

no code implementations26 Jun 2019 Holger Drees, Anne Sabourin

Within the statistical learning framework of empirical risk minimization, our main focus is to analyze the squared reconstruction error for the exceedances over large radial thresholds.

On Binary Classification in Extreme Regions

no code implementations NeurIPS 2018 Hamid Jalalzai, Stephan Clémençon, Anne Sabourin

In pattern recognition, a random label Y is to be predicted based upon observing a random vector X valued in $\mathbb{R}^d$ with d>1 by means of a classification rule with minimum probability of error.

Binary Classification Classification +1

Max K-armed bandit: On the ExtremeHunter algorithm and beyond

no code implementations27 Jul 2017 Mastane Achab, Stephan Clémençon, Aurélien Garivier, Anne Sabourin, Claire Vernade

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.

Sparsity in Multivariate Extremes with Applications to Anomaly Detection

no code implementations21 Jul 2015 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 monitoring, insurance, environmental risk management and anomaly detection.

Anomaly Detection Dimensionality Reduction +1

On Anomaly Ranking and Excess-Mass Curves

no code implementations5 Feb 2015 Nicolas Goix, Anne Sabourin, Stéphan Clémençon

Extensions to the multivariate setting are far from straightforward and it is precisely the main purpose of this paper to introduce a novel and convenient (functional) criterion for measuring the performance of a scoring function regarding the anomaly ranking task, referred to as the Excess-Mass curve (EM curve).

Anomaly Detection

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