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  1. Séminaire MODAL'X : Camille Frévent (Université de Lille)

    northern France. Moving onto the second part of the talk a new approach to the autoregressive spatial functional range of processes. The estimation problem of the model will be discussed and the new approach will be different aspect of spatial analysis of functional data. The first part will introduce a novel approach to spatial detection of functional data. This approach is based on the use of spatial scan statistics and is particularly particularly useful in environmental surveillance Given the known adverse health effects of pollutants it is crucial Recent advances for the analysis of spatial functional data

    • Type : Actualité
    • - Mis à jour le 07/01/24

  2. Séminaire MODAL'X : Vincent Divol (Université PSL/CEREMADE) (REPORTE)

    setting we solve the problem of finding the optimal unaware prediction function satisfying the demographic groups. Among the fairness criteria under consideration demographic parity is arguably the most conceptually requires that the distribution of outcomes is identical across all sensitive groups. We focus on the unawareness unawareness framework where the prediction function cannot make direct use of the sensitive attribute thus transport problem and exhibit relevant properties of the associated prediction function. Fair regression in the unaware framework using optimal transport

    • Type : Actualité
    • - Mis à jour le 06/06/24

  3. Séminaire MODAL'X : Azadeh Khaleghi (CREST, ENSAE)

    a discussion on the potential application of these results to the approximation of the optimal strategy proposed strongly consistent estimators of the 1 norm of the sequence of -mixing respectively -mixing coefficients sequences of mixing coefficients. The estimators are in turn used in the development of hypothesis tests talk I will introduce some of our recent results on the estimation of mixing coefficients from stationary Inferring the mixing properties of an ergodic process

    • Type : Actualité
    • - Mis à jour le 15/11/23

  4. Séminaire MODAL'X : Christophe Giraud (LMO, Université Paris-Saclay)

    characterizes the difficulty of bias estimation. The gap-depend rate reveals the importance of the between gap for the difficulty of the problem. Interestingly there exists non-trivial instances where the problem She receives a reward corresponding to the covariates of the action that she has chosen but only observe biased evaluation of this reward where the bias depends on the sensitive attribute. We design a Fair Phased making scenarios with higher and higher stakes. At the same time recent work has highlighted that these The price of unfairness in linear bandits with biased feedback

    • Type : Actualité
    • - Mis à jour le 11/05/22

  5. Séminaire MODAL'X : Vincent Divol (CEREMADE, Université Paris Dauphine - PSL)

    setting we solve the problem of finding the optimal unaware prediction function satisfying the demographic groups. Among the fairness criteria under consideration demographic parity is arguably the most conceptually requires that the distribution of outcomes is identical across all sensitive groups. We focus on the unawareness unawareness framework where the prediction function cannot make direct use of the sensitive attribute thus transport problem and exhibit relevant properties of the associated prediction function. Fair regression in the unaware framework using optimal transport

    • Type : Actualité
    • - Mis à jour le 02/10/24

  6. Réunion du CDPC du mois de mars 2018

    d'Amsterdam Amsterdarm School of Economics co-Founder of the Interdisciplinary Corruption Research Network donnera Présentation de thèse : The Social psychology of corruption

    • Type : Actualité
    • - Mis à jour le 20/03/18

  7. GIAMPAOLO NUVOLATI, Università Milano Bicocca / VINCENT LAISNEY, Université Paris Nanterre

    The flâneur: from past profiles to future research perspectives

    • Type : Actualité
    • - Mis à jour le 08/11/19

  8. Séminaire MODAL'X : Marie Perrot-Dockes (MAP5)

    multivariate mixture models. The estimator that this methodology proposes computes the marginal likelihood from where the true marginal likelihood is available analytically. It performs well against state-of-the-art is based on an asymptotically optimal ordering of the parameter space which can in turn be used to provide model selection on univariate and multivariate data sets. Efficiently Computed Marginal Likelihoods using the THAMES Estimator

    • Type : Actualité
    • - Mis à jour le 13/01/26

  9. Séminaire MODAL'X : Brune Massoulié (CEREMADE)

    Résumé The lifted TASEP is a variant of the totally asymmetric exclusion process where at each time-step reversible dynamics. We will study the behaviour of this system on the integer line by evidencing a connexion marked particle tries to move forward then may pass the marker to another particle. It was introduced by true self-avoiding walks yielding timescales of the dynamics. This is based on joint work with Clément From the lifted TASEP to true self-avoiding walks

    • Type : Actualité
    • - Mis à jour le 19/01/26

  10. Droit

    Privacy's blueprint : the battle to control the design of new technologies Publishing copyright 2018. Privacy's blueprint the battle to control the design of new technologies W. Hartzog Privacy's blueprint : the battle to control the design of new technologies Privacy's blueprint : the battle to control the design of new technologies

    • Type : Page libre
    • - Mis à jour le 13/05/19