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CVPR
2010
IEEE
14 years 5 months ago
Efficient Piecewise Learning for Conditional Random Fields
Conditional Random Field models have proved effective for several low-level computer vision problems. Inference in these models involves solving a combinatorial optimization probl...
Karteek Alahari, Phil Torr
IJAHUC
2008
118views more  IJAHUC 2008»
13 years 10 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
CPC
2002
95views more  CPC 2002»
13 years 10 months ago
Permutation Pseudographs And Contiguity
The space of permutation pseudographs is a probabilistic model of 2-regular pseudographs on n vertices, where a pseudograph is produced by choosing a permutation of {1, 2, . . . ...
Catherine S. Greenhill, Svante Janson, Jeong Han K...
CONNECTION
2006
101views more  CONNECTION 2006»
13 years 10 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
SDM
2008
SIAM
138views Data Mining» more  SDM 2008»
13 years 11 months ago
Clustering from Constraint Graphs
In constrained clustering it is common to model the pairwise constraints as edges on the graph of observations. Using results from graph theory, we analyze such constraint graphs ...
Ari Freund, Dan Pelleg, Yossi Richter