Paris Dauphine University

About: Paris Dauphine University is a education organization based out in Paris, France. It is known for research contribution in the topics: Context (language use) & Population. The organization has 1766 authors who have published 6909 publications receiving 162747 citations. The organization is also known as: Paris Dauphine & Dauphine.

Existence for a Three-Dimensional Steady State Fluid-Structure Interaction Problem

Abstract: A steady state fluid-structure interaction problem is considered and its solvability is studied. Both the fluid and the structure are three-dimensional. The equations of the viscous fluid motion are set in an unknown domain depending on the structure displacement. The structure is elastic and its deformation depends on the stress coming from the fluid. We prove that, for small enough applied exterior forces, there exists at least one regular solution of this nonlinear coupled problem.

Ranking scientists and departments in a consistent manner

Abstract: The standard data that we use when computing bibliometric rankings of scientists are just their publication/citation records, i.e., so many papers with 0 citation, so many with 1 citation, so many with 2 citations, etc. The standard data for bibliometric rankings of departments have the same structure. It is therefore tempting (and many authors gave in to temptation) to use the same method for computing rankings of scientists and rankings of departments. Depending on the method, this can yield quite surprising and unpleasant results. Indeed, with some methods, it may happen that the "best" department contains the "worst" scientists, and only them. This problem will not occur if the rankings satisfy a property called consistency, recently introduced in the literature. In this paper, we explore the consequences of consistency and we characterize two families of consistent rankings.

SD-Rtree: A Scalable Distributed Rtree

Abstract: We propose a scalable distributed data structure (SDDS) called SD-Rtree. We intend our structure for point and window queries over possibly large spatial datasets distributed on clusters of interconnected servers. SD-Rtree generalizes the well-known Rtree structure. It uses a distributed balanced binary spatial tree that scales with insertions to potentially any number of storage servers through splits of the overloaded ones. A user/application manipulates the structure from a client node. The client addresses the tree through its image that the splits can make outdated. This may generate addressing errors, solved by the forwarding among the servers. Specific messages towards the clients incrementally correct the outdated images.

Robust Fundamental Theorem for Continuous Processes

Abstract: We study a continuous-time financial market with continuous price processes under model uncertainty, modeled via a family inline image of possible physical measures. A robust notion inline image of no-arbitrage of the first kind is introduced; it postulates that a nonnegative, nonvanishing claim cannot be superhedged for free by using simple trading strategies. Our first main result is a version of the fundamental theorem of asset pricing: inline image holds if and only if every inline image admits a martingale measure that is equivalent up to a certain lifetime. The second main result provides the existence of optimal superhedging strategies for general contingent claims and a representation of the superhedging price in terms of martingale measures.