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: Why modular approaches might be preferable to the full model in misspecified settings is investigated and a principled criteria to choose between modular and full-model approaches is proposed.
Abstract: In modern applications, statisticians are faced with integrating heterogeneous data modalities relevant for an inference, prediction, or decision problem. In such circumstances, it is convenient to use a graphical model to represent the statistical dependencies, via a set of connected "modules", each relating to a specific data modality, and drawing on specific domain expertise in their development. In principle, given data, the conventional statistical update then allows for coherent uncertainty quantification and information propagation through and across the modules. However, misspecification of any module can contaminate the estimate and update of others, often in unpredictable ways. In various settings, particularly when certain modules are trusted more than others, practitioners have preferred to avoid learning with the full model in favor of approaches that restrict the information propagation between modules, for example by restricting propagation to only particular directions along the edges of the graph. In this article, we investigate why these modular approaches might be preferable to the full model in misspecified settings. We propose principled criteria to choose between modular and full-model approaches. The question arises in many applied settings, including large stochastic dynamical systems, meta-analysis, epidemiological models, air pollution models, pharmacokinetics-pharmacodynamics, and causal inference with propensity scores.
70 citations
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TL;DR: In this article, it was shown that the ex ante incentive compatible core of an exchange economy with private information is always non-empty, even if utility functions are quasi-linear.
Abstract: The ex ante incentive compatible core of an exchange economy with private information is the (standard) core of a socially designed characteristic function, which expresses the fact that coalitions allocate goods by means of random incentive compatible mechanisms. We first survey some results in the case of perfectly divisible goods. Examples then show that the ex ante incentive compatible core can be empty, even if utility functions are quasi-linear. If, in addition to quasi-linearity, further assumptions are made (like independent private values), the non-emptiness of the core follows nevertheless from d'Aspremont and Gerard-Varet's construction of incentive compatible, ex post efficient mechanisms. We also introduce a private information version of Shapley and Scarf's economies with indivisible goods, and prove that the ex ante incentive compatible core is always non-empty in this framework.
70 citations
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TL;DR: In this paper, the authors analyze the factors that drive the adoption of innovative resource efficiency strategies to reduce energy and material use, under different market conditions, and uncover the paradox of lower adoption of resource efficiency strategy in an economic downturn and identify the characteristics of firms that adopt these strategies.
70 citations
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TL;DR: In this paper, the authors introduce a minimal flow-like variational problem whose solution is characterized by a very degenerate elliptic PDE and prove regularity results for the degenerate EDE.
70 citations
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12 Jul 2011TL;DR: Six judgment aggregation rules are studied; two of them, based on distances, have been previously defined; the other four are new, and all inspired both by voting theory and knowledge representation and reasoning, and address some of their social choice theoretic properties.
Abstract: Many voting rules are based on some minimization principle. Likewise, in the field of logic-based knowledge representation and reasoning, many belief change or inconsistency handling operators also make use of minimization. Surprisingly, minimization has not played a major role in the field of judgment aggregation, in spite of its proximity to voting theory and logic-based knowledge representation and reasoning. Here we make a step in this direction and study six judgment aggregation rules; two of them, based on distances, have been previously defined; the other four are new, and all inspired both by voting theory and knowledge representation and reasoning. We study the inclusion relationships between these rules and address some of their social choice theoretic properties.
70 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 |