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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
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
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
d'Amsterdam Amsterdarm School of Economics co-Founder of the Interdisciplinary Corruption Research Network donnera Présentation de thèse : The Social psychology of corruption
The flâneur: from past profiles to future research perspectives
sociolects of the Russophone Ukrainian underworld in the early part of the 20th century. For his translations Russophone literature to the work of writers who have chronicled colorfully life on the margins of society rendering the bravura hardboiled styles of Isaac Babel and Andrey Kurkov who make rich use of the sociolects Ukrainian Dralyuk drew on the literary legacy of Jewish-American writers from the 1920s and 1930s some of mined the stylistic repertoire of Dashiell Hammett Raymond Chandler and lesser known members of the Black "Out of the Past: Translating Historical Crime Fiction"
novel approach for learning with such data called the signature transform and rooted in rough path theory graded feature set of their iterated integrals called the signature. After a general overview of signatures infinite series. Therefore we define an estimator of the truncation order and provide theoretical guarantees by showing on both simulated and real-world data the advantage of a signature-based regression model compared compared to traditional functional models when the data is highly dimensional. Learning from data streams with the signature transform
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 Efficiently Computed Marginal Likelihoods using the THAMES Estimator
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
