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08/02/2023
Regular Variation in Hilbert Spaces and Principal Component Analysis for Functional Extremes
Motivated by the increasing availability of data of functional nature, w...
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05/17/2023
Towards More Robust NLP System Evaluation: Handling Missing Scores in Benchmarks
The evaluation of natural language processing (NLP) systems is crucial f...
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03/22/2023
Robust Consensus in Ranking Data Analysis: Definitions, Properties and Computational Issues
As the issue of robustness in AI systems becomes vital, statistical lear...
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03/06/2023
On Regression in Extreme Regions
In the classic regression problem, the value of a real-valued random var...
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02/07/2023
A Bipartite Ranking Approach to the Two-Sample Problem
The two-sample problem, which consists in testing whether independent sa...
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11/14/2022
Assessing Performance and Fairness Metrics in Face Recognition - Bootstrap Methods
The ROC curve is the major tool for assessing not only the performance b...
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11/01/2022
On Medians of (Randomized) Pairwise Means
Tournament procedures, recently introduced in Lugosi Mendelson (2016...
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10/24/2022
Mitigating Gender Bias in Face Recognition Using the von Mises-Fisher Mixture Model
In spite of the high performance and reliability of deep learning algori...
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02/23/2022
EMOTHAW: A novel database for emotional state recognition from handwriting
The detection of negative emotions through daily activities such as hand...
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02/15/2022
A Statistical Learning View of Simple Kriging
In the Big Data era, with the ubiquity of geolocation sensors in particu...
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02/08/2022
What are the best systems? New perspectives on NLP Benchmarking
In Machine Learning, a benchmark refers to an ensemble of datasets assoc...
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01/20/2022
Statistical Depth Functions for Ranking Distributions: Definitions, Statistical Learning and Applications
The concept of median/consensus has been widely investigated in order to...
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01/17/2022
Improving the quality control of seismic data through active learning
In image denoising problems, the increasing density of available images ...
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01/13/2022
Functional Anomaly Detection: a Benchmark Study
The increasing automation in many areas of the Industry expressly demand...
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09/20/2021
Learning to Rank Anomalies: Scalar Performance Criteria and Maximization of Two-Sample Rank Statistics
The ability to collect and store ever more massive databases has been ac...
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09/06/2021
Visual Recognition with Deep Learning from Biased Image Datasets
In practice, and more especially when training deep neural networks, vis...
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07/27/2021
Individual Survival Curves with Conditional Normalizing Flows
Survival analysis, or time-to-event modelling, is a classical statistica...
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06/21/2021
Affine-Invariant Integrated Rank-Weighted Depth: Definition, Properties and Finite Sample Analysis
Because it determines a center-outward ordering of observations in ℝ^d w...
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04/07/2021
Concentration bounds for the empirical angular measure with statistical learning applications
The angular measure on the unit sphere characterizes the first-order dep...
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04/07/2021
Concentration Inequalities for Two-Sample Rank Processes with Application to Bipartite Ranking
The ROC curve is the gold standard for measuring the performance of a te...
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03/29/2021
Dynamically Modelling Heterogeneous Higher-Order Interactions for Malicious Behavior Detection in Event Logs
Anomaly detection in event logs is a promising approach for intrusion de...
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03/23/2021
Depth-based pseudo-metrics between probability distributions
Data depth is a non parametric statistical tool that measures centrality...
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06/26/2020
Nearest Neighbour Based Estimates of Gradients: Sharp Nonasymptotic Bounds and Applications
Motivated by a wide variety of applications, ranging from stochastic opt...
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06/09/2020
How Robust is the Median-of-Means? Concentration Bounds in Presence of Outliers
In contrast to the empirical mean, the Median-of-Means (MoM) is an estim...
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03/13/2020
Flexible and Context-Specific AI Explainability: A Multidisciplinary Approach
The recent enthusiasm for artificial intelligence (AI) is due principall...
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02/21/2020
A Multiclass Classification Approach to Label Ranking
In multiclass classification, the goal is to learn how to predict a rand...
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02/19/2020
Learning Fair Scoring Functions: Fairness Definitions, Algorithms and Generalization Bounds for Bipartite Ranking
Many applications of artificial intelligence, ranging from credit lendin...
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02/12/2020
Weighted Empirical Risk Minimization: Sample Selection Bias Correction based on Importance Sampling
We consider statistical learning problems, when the distribution P' of t...
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10/09/2019
The Area of the Convex Hull of Sampled Curves: a Robust Functional Statistical Depth Measure
With the ubiquity of sensors in the IoT era, statistical observations ar...
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07/17/2019
A Multivariate Extreme Value Theory Approach to Anomaly Clustering and Visualization
In a wide variety of situations, anomalies in the behaviour of a complex...
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06/28/2019
Statistical Learning from Biased Training Samples
With the deluge of digitized information in the Big Data era, massive da...
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06/21/2019
On Tree-based Methods for Similarity Learning
In many situations, the choice of an adequate similarity measure or metr...
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06/21/2019
Trade-offs in Large-Scale Distributed Tuplewise Estimation and Learning
The development of cluster computing frameworks has allowed practitioner...
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06/05/2019
Empirical Risk Minimization under Random Censorship: Theory and Practice
We consider the classic supervised learning problem, where a continuous ...
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04/09/2019
Functional Isolation Forest
For the purpose of monitoring the behavior of complex infrastructures (e...
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10/15/2018
Dimensionality Reduction and (Bucket) Ranking: a Mass Transportation Approach
Whereas most dimensionality reduction techniques (e.g. PCA, ICA, NMF) fo...
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07/18/2018
A Probabilistic Theory of Supervised Similarity Learning for Pointwise ROC Curve Optimization
The performance of many machine learning techniques depends on the choic...
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05/28/2018
Autoencoding any Data through Kernel Autoencoders
This paper investigates a novel algorithmic approach to data representat...
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05/08/2018
Profitable Bandits
Originally motivated by default risk management applications, this paper...
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01/17/2018
Ranking Data with Continuous Labels through Oriented Recursive Partitions
We formulate a supervised learning problem, referred to as continuous ra...
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10/31/2017
Ranking Median Regression: Learning to Order through Local Consensus
This article is devoted to the problem of predicting the value taken by ...
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07/27/2017
Max K-armed bandit: On the ExtremeHunter algorithm and beyond
This paper is devoted to the study of the max K-armed bandit problem, wh...
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05/03/2017
Mass Volume Curves and Anomaly Ranking
This paper aims at formulating the issue of ranking multivariate unlabel...
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06/08/2016
Gossip Dual Averaging for Decentralized Optimization of Pairwise Functions
In decentralized networks (of sensors, connected objects, etc.), there i...
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03/31/2016
Sparse Representation of Multivariate Extremes with Applications to Anomaly Ranking
Extremes play a special role in Anomaly Detection. Beyond inference and ...
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11/17/2015
Extending Gossip Algorithms to Distributed Estimation of U-Statistics
Efficient and robust algorithms for decentralized estimation in networks...
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08/25/2015
AUC Optimisation and Collaborative Filtering
In recommendation systems, one is interested in the ranking of the predi...
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02/05/2015
On Anomaly Ranking and Excess-Mass Curves
Learning how to rank multivariate unlabeled observations depending on th...
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01/12/2015
Scaling-up Empirical Risk Minimization: Optimization of Incomplete U-statistics
In a wide range of statistical learning problems such as ranking, cluste...
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01/09/2015