Evènement pour le groupe BioInformatique et Visualisation

Date 2011-05-05  11:00-12:30
TitreResults in complex networks 
RésuméI will present two results in complex networks. The first one is a generic active learning method, applicable to networks arising in various fields. In many networks, vertices have hidden attributes that are correlated with the network’s topology. For instance, in social networks, people are more likely to be friends if they are demographically similar. In food webs, predators typically eat prey of lower body mass. We explore a setting in which the network’s topology is known, but these attributes are not. If each vertex can be queried, learning the value of its hidden attributes —but only at some cost— then we need an algorithm which chooses which vertex to query next, in order to learn as much as possible about the attributes of the remaining vertices. We present two heuristics and assess their results. The second one is an application of complex network methods to epistemology. Thanks to a large database of 200K articles, we empirically study the “complex systems” field and its claims to find universal principles applying to systems in general. Study of the references shared by the papers allows us to obtain a global point of view on the structure of this highly interdisciplinary field. We show that its overall coherence does not arise from a universal theory but instead from computational techniques and fruitful adaptations of the idea of self-organization to specific systems. At a more local level, specifically interdisciplinary, we find that understanding between vastly different scientific cultures is possible thanks to “trading zones”, i.e. sub-communities that manage to work at the interface around specific tools (e.g. a DNA microchip) or concepts (a network). 
Lieu178 (LaBRI) 
OrateurJean-Baptiste Rouquier 

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