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: 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.

Strategy-proof mechanisms for facility location games with many facilities

Abstract: This paper is devoted to the location of public facilities in a metric space. Selfish agents are located in this metric space, and their aim is to minimize their own cost, which is the distance from their location to the nearest facility. A central authority has to locate the facilities in the space, but she is ignorant of the true locations of the agents. The agents will therefore report their locations, but they may lie if they have an incentive to do it. We consider two social costs in this paper: the sum of the distances of the agents to their nearest facility, or the maximal distance of an agent to her nearest facility. We are interested in designing strategy-proof mechanisms that have a small approximation ratio for the considered social cost. A mechanism is strategy-proof if no agent has an incentive to report false information. In this paper, we design strategyproof mechanisms to locate n - 1 facilities for n agents. We study this problem in the general metric and in the tree metric spaces. We provide lower and upper bounds on the approximation ratio of deterministic and randomized strategy-proof mechanisms.

A recursive point process model for infectious diseases

Abstract: We introduce a new type of point process model to describe the incidence of contagious diseases. The model incorporates the premise that when a disease occurs at low frequency in the population, such as in the primary stages of an outbreak, then anyone with the disease is likely to have a high rate of transmission to others, whereas when the disease is prevalent, the transmission rate is lower due to prevention measures and a relatively high percentage of previous exposure in the population. The model is said to be recursive, in the sense that the conditional intensity at any time depends on the productivity associated with previous points, and this productivity in turn depends on the conditional intensity at those points. Basic properties of the model are derived, estimation and simulation are discussed, and the recursive model is shown to fit well to California Rocky Mountain Spotted Fever data.

QoS-Driven Selection of Web Services for Transactional Composition

Abstract: Web services composition has been gaining interest over the last years as it leverages the capabilities to offer complex operations resulting from the aggregation of Web services offered by different organizations. As composite Web services are often long-running, loosely coupled and cross-organizational applications, advanced transactional support is required to ensure reliable execution. In addition, in the presence of multiple Web services with equivalent functionality, users will discriminate the alternatives based on their quality of service (QoS). This paper address the issue of selecting and composing Web services not only according to their functional requirements but also to their transactional properties and QoS characteristics defined using a quality model. In this model, Web services are selected in a way that satisfies user preferences. These preferences are expressed as weights over QoS criterion and as risk level defining semantically the transactional requirements.