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 aim of this paper is to generalize the way of computing the credibility of outranking in a multiple criteria aggregation procedure, in view of taking into account two new effects called reinforced preference and counter-veto, which remains compatible with the handling of ordinal preference scales.
71 citations
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TL;DR: The real object size implied by a word appears to be primarily encoded in early visual regions, while the taxonomic category and sub-categorical cluster in more anterior temporal regions, indicating that different areas along the ventral stream encode complementary dimensions of the semantic space.
71 citations
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23 Jun 2008TL;DR: This paper considers an Ultrametric Contour Map, the representation of a hierarchy of segmentations as a real-valued boundary image, and proposes an algorithm for constructing Voronoi tessellations with respect to a distance defined by the UCM.
Abstract: In this paper, we address the problem of constrained segmentation of natural images, in which a human user places one seed point inside each object of interest in the image and the task is to determine the object boundaries. For this purpose, we study the connection between seed-based and hierarchical segmentation. We consider an Ultrametric Contour Map (UCM), the representation of a hierarchy of segmentations as a real-valued boundary image. Starting from a set of seed points, we propose an algorithm for constructing Voronoi tessellations with respect to a distance defined by the UCM. As a result, the main contribution of the paper is a method that allows exploiting the information of any hierarchical scheme for constrained segmentation. Our algorithm is parameter-free, computationally efficient and robust. We prove the interest of the approach proposed by evaluating quantitatively the results with respect to ground-truth data.
70 citations
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06 Jan 2007TL;DR: This work shows how to set up a distributed negotiation framework that will allow a group of agents to reach an allocation of goods that is both efficient and envy-free.
Abstract: Mechanisms for dividing a set of goods amongst a number of autonomous agents need to balance efficiency and fairness requirements. A common interpretation of fairness is envy-freeness, while efficiency is usually understood as yielding maximal overall utility. We show how to set up a distributed negotiation framework that will allow a group of agents to reach an allocation of goods that is both efficient and envy-free.
70 citations
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TL;DR: In this paper, a polynomial approximation theory linked to combinatorial optimization is defined and a notion of equivalence among optimization problems is introduced, which includes translation or affine transformation of the objective function or yet some aspects of equivalencies between maximization and minimization problems.
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 |