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NIPS
2008
13 years 8 months ago
Non-stationary dynamic Bayesian networks
Abstract: Structure learning of dynamic Bayesian networks provide a principled mechanism for identifying conditional dependencies in time-series data. This learning procedure assum...
Joshua W. Robinson, Alexander J. Hartemink
ICCV
2009
IEEE
14 years 10 months ago
The Swap and Expansion Moves Revisited and Fused
Many solutions to computer vision and image processing problems involve the minimization of multi-label energy functions with up to K variables in each term. In the minimization pr...
Ido Leichter
CVPR
2007
IEEE
14 years 9 months ago
Large scale vision-based navigation without an accurate global reconstruction
Autonomous cars will likely play an important role in the future. A vision system designed to support outdoor navigation for such vehicles has to deal with large dynamic environme...
Albert Diosi, Anthony Remazeilles, François...
VIS
2005
IEEE
122views Visualization» more  VIS 2005»
14 years 8 months ago
Effectively Visualizing Large Networks Through Sampling
We study the problem of visualizing large networks and develop es for effectively abstracting a network and reducing the size to a level that can be clearly viewed. Our size reduc...
Davood Rafiei, Stephen Curial
ICML
2007
IEEE
14 years 8 months ago
Learning distance function by coding similarity
We consider the problem of learning a similarity function from a set of positive equivalence constraints, i.e. 'similar' point pairs. We define the similarity in informa...
Aharon Bar-Hillel, Daphna Weinshall