Institution
Paris Dauphine University
Education•Paris, France•
About: Paris Dauphine University is a education organization based out in Paris, France. It is known for research contribution in the topics: Population & Approximation algorithm. The organization has 1766 authors who have published 6909 publications receiving 162747 citations. The organization is also known as: Paris Dauphine & Dauphine.
Topics: Population, Approximation algorithm, Bounded function, Parameterized complexity, Time complexity
Papers published on a yearly basis
Papers
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TL;DR: The Hamiltoniens sousquadratiques. Commande stochastic optimale optimale avec contraintes d'etat as mentioned in this paper, a.k.a. Hamiltoniens superquadratique.
Abstract: Hamiltoniens sousquadratiques. Conditions aux limites infinies et donnees d'explosion. Hamiltoniens superquadratiques. Formulation viscosite des conditions aux limites. Le probleme ergodique. Commande stochastique optimale avec contraintes d'etat
299 citations
TL;DR: In this article, the posterior distribution of a mixture model is studied in the presence of overfitting, where the number of components in the mixture is larger than the true numbers of components, a situation referred to as an overfitted mixture.
Abstract: Summary. We study the asymptotic behaviour of the posterior distribution in a mixture model when the number of components in the mixture is larger than the true number of components: a situation which is commonly referred to as an overfitted mixture. We prove in particular that quite generally the posterior distribution has a stable and interesting behaviour, since it tends to empty the extra components. This stability is achieved under some restriction on the prior, which can be used as a guideline for choosing the prior. Some simulations are presented to illustrate this behaviour.
298 citations
TL;DR: The authors show that standard theories, which build on a random growth mechanism, generate transition dynamics that are too slow relative to those observed in the data and suggest two parsimonious deviations from the canonical model that can explain such changes: scale dependence that may arise from changes in skill prices and type dependence, that is, the presence of some high-growth types.
Abstract: The past forty years have seen a rapid rise in top income inequality in the United States While there is a large number of existing theories of the Pareto tail of the long-run income distributions, almost none of these address the fast rise in top inequality observed in the data We show that standard theories, which build on a random growth mechanism, generate transition dynamics that are too slow relative to those observed in the data We then suggest two parsimonious deviations from the canonical model that can explain such changes: “scale dependence” that may arise from changes in skill prices, and “type dependence,” that is, the presence of some “high-growth types” These deviations are consistent with theories in which the increase in top income inequality is driven by the rise of “superstar” entrepreneurs or managers
297 citations
TL;DR: This article used data from a French university to analyze gender biases in student evaluations of teaching (SETs) and found that male students express a bias in favor of male professors, despite the fact that students appear to learn as much from women as from men.
296 citations
TL;DR: In this article, the authors investigated various perceived benefits of loyalty programs using a multi-benefit framework based on utilitarian, hedonic, and relationship literature and found that monetary savings, exploration, entertainment, recognition, and social benefits have different impacts on satisfaction with the loyalty program, loyalty to the program, and perceived relationship investment of the firm.
295 citations
Authors
Showing all 1819 results
| Name | H-index | Papers | Citations |
|---|---|---|---|
| Pierre-Louis Lions | 98 | 283 | 57043 |
| Laurent D. Cohen | 94 | 417 | 42709 |
| Chris Bowler | 87 | 288 | 35399 |
| Christian P. Robert | 75 | 535 | 36864 |
| Albert Cohen | 71 | 368 | 19874 |
| Gabriel Peyré | 65 | 303 | 16403 |
| Kerrie Mengersen | 65 | 737 | 20058 |
| Nader Masmoudi | 62 | 245 | 10507 |
| Roland Glowinski | 61 | 393 | 20599 |
| Jean-Michel Morel | 59 | 302 | 29134 |
| Nizar Touzi | 57 | 224 | 11018 |
| Jérôme Lang | 57 | 277 | 11332 |
| William L. Megginson | 55 | 169 | 18087 |
| Alain Bensoussan | 55 | 417 | 22704 |
| Yves Meyer | 53 | 128 | 14604 |