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» Randomization Techniques for Graphs.
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FOCS
2002
IEEE
15 years 11 months ago
Learning a Hidden Matching
We consider the problem of learning a matching (i.e., a graph in which all vertices have degree 0 or 1) in a model where the only allowed operation is to query whether a set of ve...
Noga Alon, Richard Beigel, Simon Kasif, Steven Rud...
NIPS
2003
15 years 8 months ago
Discriminative Fields for Modeling Spatial Dependencies in Natural Images
In this paper we present Discriminative Random Fields (DRF), a discriminative framework for the classification of natural image regions by incorporating neighborhood spatial depe...
Sanjiv Kumar, Martial Hebert
CONNECTION
2006
101views more  CONNECTION 2006»
15 years 6 months ago
High capacity, small world associative memory models
Models of associative memory usually have full connectivity or if diluted, random symmetric connectivity. In contrast, biological neural systems have predominantly local, non-symm...
Neil Davey, Lee Calcraft, Rod Adams
IJAHUC
2008
118views more  IJAHUC 2008»
15 years 6 months ago
Analysis models for unguided search in unstructured P2P networks
: Random walk and flooding are basic mechanisms for searching unstructured overlays. This paper shows that node coverage is an important metric for query performance in random grap...
Bin Wu, Ajay D. Kshemkalyani
CGF
2011
14 years 10 months ago
Dynamic Insets for Context-Aware Graph Navigation
Maintaining both overview and detail while navigating in graphs, such as road networks, airline route maps, or social networks, is difficult, especially when targets of interest ...
S. Ghani, N. Henry Riche, N. Elmqvist