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» The metamathematics of random graphs
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INFOCOM
2009
IEEE
15 years 8 months ago
Lightweight Coloring and Desynchronization for Networks
—We study the distributed desynchronization problem for graphs with arbitrary topology. Motivated by the severe computational limitations of sensor networks, we present a randomi...
Arik Motskin, Tim Roughgarden, Primoz Skraba, Leon...
120
Voted
CVPR
2009
IEEE
16 years 9 months ago
P-Brush: Continuous Valued MRFs with Normed Pairwise Distributions for Image Segmentation
Interactive image segmentation traditionally involves the use of algorithms such as Graph Cuts or Random Walker. Common concerns with using Graph Cuts are metrication artifacts ...
Dheeraj Singaraju, Leo Grady, René Vidal
ICML
2003
IEEE
16 years 2 months ago
Semi-Supervised Learning Using Gaussian Fields and Harmonic Functions
An approach to semi-supervised learning is proposed that is based on a Gaussian random field model. Labeled and unlabeled data are represented as vertices in a weighted graph, wit...
Xiaojin Zhu, Zoubin Ghahramani, John D. Lafferty
150
Voted
CVPR
2009
IEEE
1148views Computer Vision» more  CVPR 2009»
16 years 8 months ago
Shape Constrained Figure-Ground Segmentation and Tracking
Global shape information is an effective top-down complement to bottom-up figure-ground segmentation as well as a useful constraint to avoid drift during adaptive tracking. We p...
Zhaozheng Yin, Robert T. Collins
CORR
2010
Springer
107views Education» more  CORR 2010»
15 years 14 days ago
Maximum Betweenness Centrality: Approximability and Tractable Cases
The Maximum Betweenness Centrality problem (MBC) can be defined as follows. Given a graph find a k-element node set C that maximizes the probability of detecting communication be...
Martin Fink, Joachim Spoerhase