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classifier. In the first step the weights of the mixture are estimated in the second step an empirical risk procedure is performed to estimate the parameters of the Hawkes processes. We establish the consistency multivariate Hawkes processes. The challenge here is the high-dimension of the classification problem which can obtained consistency in support of the LASSO the consistency of the classifier. Joint work with Christophe Denis Résumé We investigate the multiclass classification problem where the features are event sequences. More
Bootstrap GSBB . The GSBB preserves the periodic structure of the data and in result the consistent estimators other fields. Periodicity is often present not only in the mean but also in the covariance function. Thus apply the GSBB one needs to know the period length. Sometimes it may happen that period length is not known can be used. We discuss the consistency of the GSBB and the EMBB for parameters associated with PC time series these are the overall mean seasonal means the autocovariance function and the Fourier coefficients
estimation. The gap-depend rate reveals the importance of the between group gap for the difficulty of the problem instances where the problem is no more difficult than its unbiased counterpart. This is a joint work with 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 worst case up to possible log terms . The worst case regret is shown to be much larger than in classical The price of unfairness in linear bandits with biased feedback
weights if the weights are atomless the maximum weight matching is uniquely defined. We study the asymptotic object of the graph called the unimodular Bienaymé Galton Watson tree. We also show when the weights are This work is a continuation of the objective method introduced by D. Aldous in 2000 and is based on two show that the optimum matching seen as a geometric graph converges locally to a matching on the limiting are atomic the convergence of the tiebreaked maximum weight matching. This convergence generalizes to
This is a book about the need to revisit and make sense of the past in order to move into the future Following the unexpected death of her father she is thrown into crisis but then she meets the enigmatic after a stranger s cat she is not expecting her life to change At 35 Ella is no longer excited by her academic becomes bound up with the stories of two other Englishwomen in France she finds the freedom to tread an enigmatic Max. Over the course of a summer their romance deepens until she makes a discovery which throws everything
des États-Unis 15 Boulevard Jourdan 75014 Paris RER Cité Université Tram Cité Universitaire auteur de Frame 1971 1990 Progress Under Erasure Bad History et poursuit actuellement la composition de le volume A Guide to Poetics Journal Writing in the Expanded Field 1982 1998 dir. Hejinian et Watten volumes d essais critiques Total Syntax Illinois 1985 The Constructivist Moment From Material Text to Cultural volumes composé par dix membres du mouvement Language The Grand Piano. An Experiment in Collective Autobiography hybride entre poésie et prose dont l unité est la phrase le vers remodelé vers une possibilité narrative Recherches Anglophones CREA EA 370 de l'Université Paris Nanterre de l Université Paris-Diderot LARCA et de l École
Adams U. Sydney Elsa Devienne Politiques américaines CREA U. Paris Nanterre et Andrew Kahrl U. Virginia le groupe Culture Cultures Maud Simonet sociologue U. Paris Nanterre présentera une communication intitulée Places and Cultures of Capitalism New Histories from the Grassroots mené par le CREA Politiques américaines Places and Cultures of Capitalism New Histories at the Grassroots . Avec notamment les interventions de Brenda Parker Dept. of Urban Planning and Policy U. Illinois at Chicago . 13h30-17h30 salle R13 Co-organisation
Algorithmic Fairness is an established area of machine learning willing to reduce the influence of hidden hidden bias in the data.Yet despite its wide range of applications very few works consider the multi-class setting from the fairness perspective.In this talk we focus on this question and extend the definition fairness in the case of Demographic Parity to multi-class classification.We specify the corresponding expressions of the optimal fair classifiers and describe a post-processing approach based on the plug-in principle
chains are introduced for the beta null recurrent case. A variation of the Central Limit Theorem for for a random number of summands is also presented.
scalar reward is obtained and vector-valued costs are suffered. The goal is to maximize the cumulative rewards strategy is direct and it relies on a careful adaptive tuning of the step size. The approach is inspired had so far to be at least of order T 3 4 where T is the number of rounds and were even typically assumed linearly on T. Elaborating on the main technical challenge and drawback of the previous approaches I will projected-gradient-descent updates that is able to deal with total-cost constraints of the order of T 1 2 up to poly-logarithmic
