
Transportbased Counterfactual Models
Counterfactual frameworks have grown popular in explainable and fair mac...
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Fairness seen as Global Sensitivity Analysis
Ensuring that a predictor is not biased against a sensible feature is th...
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A Consistent Extension of Discrete Optimal Transport Maps for Machine Learning Applications
Optimal transport maps define a onetoone correspondence between probab...
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Central Limit Theorems for General Transportation Costs
We consider the problem of optimal transportation with general cost betw...
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DiversityPreserving KArmed Bandits, Revisited
We consider the banditbased framework for diversitypreserving recommen...
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Risk Measures Estimation Under Wasserstein Barycenter
Randomness in financial markets requires modern and robust multivariate ...
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Achieving robustness in classification using optimal transport with hinge regularization
We propose a new framework for robust binary classification, with Deep N...
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The statistical effect of entropic regularization in optimal transportation
We propose to tackle the problem of understanding the effect of regulari...
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Review of Mathematical frameworks for Fairness in Machine Learning
A review of the main fairness definitions and fair learning methodologie...
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Projection to Fairness in Statistical Learning
In the context of regression, we consider the fundamental question of ma...
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The price for fairness in a regression framework
We consider the problem of achieving fairness in a regression framework....
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A survey of bias in Machine Learning through the prism of Statistical Parity for the Adult Data Set
Applications based on Machine Learning models have now become an indispe...
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Minimax optimal goodnessoffit testing for densities under a local differential privacy constraint
Finding anonymization mechanisms to protect personal data is at the hear...
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Using Wasserstein2 regularization to ensure fair decisions with NeuralNetwork classifiers
In this paper, we propose a new method to build fair NeuralNetwork clas...
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optimalFlow: Optimaltransport approach to flow cytometry gating and population matching
Data used in Flow Cytometry present pronounced variability due to biolog...
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AttractionRepulsion clustering with applications to fairness
In the framework of fair learning, we consider clustering methods that a...
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Entropic Variable Boosting for Explainability and Interpretability in Machine Learning
In this paper, we present a new explainability formalism to make clear t...
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Can everyday AI be ethical. Fairness of Machine Learning Algorithms
Combining big data and machine learning algorithms, the power of automat...
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A Central Limit Theorem for L_p transportation cost with applications to Fairness Assessment in Machine Learning
We provide a Central Limit Theorem for the MongeKantorovich distance be...
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Confidence Intervals for Testing Disparate Impact in Fair Learning
We provide the asymptotic distribution of the major indexes used in the ...
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Risk Measures and Credit Risk Under the BetaKotz Distribution
This paper considers the use for ValueatRisk computations of the soca...
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Obtaining fairness using optimal transport theory
Statistical algorithms are usually helping in making decisions in many a...
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COREclust: a new package for a robust and scalable analysis of complex data
In this paper, we present a new R package COREclust dedicated to the det...
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Gaussian Process Forecast with multidimensional distributional entries
In this work, we propose to define Gaussian Processes indexed by multidi...
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Gaussian Processes indexed on the symmetric group: prediction and learning
In the framework of the supervised learning of a real function defined o...
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Multiple testing for outlier detection in functional data
We propose a novel procedure for outlier detection in functional data, i...
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Deep Learning applied to Road Traffic Speed forecasting
In this paper, we propose deep learning architectures (FNN, CNN and LSTM...
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Gaussian Process Regression Model for Distribution Inputs
MongeKantorovich distances, otherwise known as Wasserstein distances, h...
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Destination Prediction by Trajectory Distribution Based Model
In this paper we propose a new method to predict the final destination o...
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Review and Perspective for Distance Based Trajectory Clustering
In this paper we tackle the issue of clustering trajectories of geolocal...
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Modeling Weather Conditions Consequences on Road Trafficking Behaviors
We provide a model to understand how adverse weather conditions modify t...
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JeanMichel Loubes
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