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Institution

Paris Dauphine University

EducationParis, 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.


Papers
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Journal ArticleDOI
TL;DR: In this paper, it was shown that the viability kernel of K under F can be approached by a sequence of discrete viability kernels associated withxn+1 źGź(xn) whereźg(x) =x + (ML/2) ź2ź.
Abstract: We study recursive inclusionsxn+1ź G(xn). For instance, such systems appear for discrete finite-difference inclusionsxn+1 źGź(xn) whereGź:=1+źF. The discrete viability kernel ofGź, i.e., the largest discrete viability domain, can be an internal approximation of the viability kernel ofK underF. We study discrete and finite dynamical systems. In the Lipschitz case we get a generalization to differential inclusions of the Euler and Runge-Kutta methods. We prove first that the viability kernel ofK underF can be approached by a sequence of discrete viability kernels associated withxn+1 źźź(xn) whereźź(x) =x + źF(x) + (ML/2) ź2ź. Secondly, we show that it can be approached by finite viability kernels associated withxhn+1 ź (źź(xhn+1) +ź(hź) źXh.

311 citations

Journal ArticleDOI
TL;DR: Under natural hypothesis on the set of all solutions to the problem obtained when the parameter varies, it is proved that three greedy algorithms converge; the last algorithm, based on the use of an a posteriori estimator, is the approach actually employed in the calculations.
Abstract: The convergence and efficiency of the reduced basis method used for the approximation of the solutions to a class of problems written as a parametrized PDE depends heavily on the choice of the elements that constitute the "reduced basis". The purpose of this paper is to analyze the a priori convergence for one of the approaches used for the selection of these elements, the greedy algorithm. Under natural hypothesis on the set of all solutions to the problem obtained when the parameter varies, we prove that three greedy algorithms converge; the last algorithm, based on the use of an a posteriori estimator, is the approach actually employed in the calculations.

308 citations

Journal ArticleDOI
TL;DR: Conditions are derived that allow one to determine whether a set of states is viable or invariant under the action of an impulse differential inclusion and methods are developed for approximating their viability and invariance kernels.
Abstract: Impulse differential inclusions are introduced as a framework for modeling hybrid phenomena. Connections to standard problems in the area of hybrid systems are discussed. Conditions are derived that allow one to determine whether a set of states is viable or invariant under the action of an impulse differential inclusion. For sets that violate these conditions, methods are developed for approximating their viability and invariance kernels, that is the largest subset that is viable or invariant under the action of the impulse differential inclusion. The results are demonstrated on examples.

308 citations

Journal ArticleDOI
TL;DR: An adaptive algorithm that iteratively updates both the weights and component parameters of a mixture importance sampling density so as to optimise the performance of importance sampling, as measured by an entropy criterion is proposed.
Abstract: In this paper, we propose an adaptive algorithm that iteratively updates both the weights and component parameters of a mixture importance sampling density so as to optimise the performance of importance sampling, as measured by an entropy criterion. The method, called M-PMC, is shown to be applicable to a wide class of importance sampling densities, which includes in particular mixtures of multivariate Student t distributions. The performance of the proposed scheme is studied on both artificial and real examples, highlighting in particular the benefit of a novel Rao-Blackwellisation device which can be easily incorporated in the updating scheme.

302 citations

Journal ArticleDOI
TL;DR: Main characteristics of ELECTRE (ELimination Et Choix Traduisant la REalite - ELimination and Choice Expressing the REality) family methods, designed for multiple criteria decision aiding, are presented.
Abstract: We present main characteristics of ELECTRE (ELimination Et Choix Traduisant la REalite - ELimination and Choice Expressing the REality) family methods, designed for multiple criteria decision aiding. These methods use as a preference model an outranking relation on the set of actions—it is constructed in result of concordance and nondiscordance tests involving a specific input preference information. After a brief description of the constructivist conception in which the ELECTRE methods are inserted, we present the main features of these methods. We discuss such characteristic features as the possibility of taking into account positive and negative reasons in the modelling of preferences, without requiring commensurable performance scales; the use of discriminating thresholds for taking into account the imperfect knowledge of data; the absence of systematic compensation between ‘gains’ and ‘losses’. The main weaknesses are also presented. Then, some aspects related to new developments are outlined. These are related to some new methodological developments, new procedures, axiomatic analysis, software tools and several other aspects. This paper is an updated version of a chapter published by the authors under the title ‘ Electre Methods: Main Features and Recent Developments’ in C. Zopounidis and P. Pardalos (Editors): Handbook of Multicriteria Analysis, Springer, Berlin 2010, pp. 51–89. Copyright © 2012 John Wiley & Sons, Ltd.

300 citations


Authors

Showing all 1819 results

NameH-indexPapersCitations
Pierre-Louis Lions9828357043
Laurent D. Cohen9441742709
Chris Bowler8728835399
Christian P. Robert7553536864
Albert Cohen7136819874
Gabriel Peyré6530316403
Kerrie Mengersen6573720058
Nader Masmoudi6224510507
Roland Glowinski6139320599
Jean-Michel Morel5930229134
Nizar Touzi5722411018
Jérôme Lang5727711332
William L. Megginson5516918087
Alain Bensoussan5541722704
Yves Meyer5312814604
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202317
202291
2021371
2020408
2019415
2018392