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» A mixture model for random graphs
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IBPRIA
2007
Springer
14 years 1 months ago
Bayesian Oil Spill Segmentation of SAR Images Via Graph Cuts
Abstract. This paper extends and generalizes the Bayesian semisupervised segmentation algorithm [1] for oil spill detection using SAR images. In the base algorithm on which we buil...
Sónia Pelizzari, José M. Bioucas-Dia...
ICA
2007
Springer
14 years 1 months ago
Modeling and Estimation of Dependent Subspaces with Non-radially Symmetric and Skewed Densities
We extend the Gaussian scale mixture model of dependent subspace source densities to include non-radially symmetric densities using Generalized Gaussian random variables linked by ...
Jason A. Palmer, Kenneth Kreutz-Delgado, Bhaskar D...
RSA
2006
69views more  RSA 2006»
13 years 7 months ago
On smoothed analysis in dense graphs and formulas
: We study a model of random graphs, where a random instance is obtained by adding random edges to a large graph of a given density. The research on this model has been started by ...
Michael Krivelevich, Benny Sudakov, Prasad Tetali
TIT
2002
129views more  TIT 2002»
13 years 7 months ago
Arbitrary source models and Bayesian codebooks in rate-distortion theory
-- We characterize the best achievable performance of lossy compression algorithms operating on arbitrary random sources, and with respect to general distortion measures. Direct an...
Ioannis Kontoyiannis, Junshan Zhang
SDM
2012
SIAM
278views Data Mining» more  SDM 2012»
11 years 10 months ago
Legislative Prediction via Random Walks over a Heterogeneous Graph
In this article, we propose a random walk-based model to predict legislators’ votes on a set of bills. In particular, we first convert roll call data, i.e. the recorded votes a...
Jun Wang, Kush R. Varshney, Aleksandra Mojsilovic