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EMMCVPR
2007
Springer
14 years 2 months ago
Bayesian Order-Adaptive Clustering for Video Segmentation
Video segmentation requires the partitioning of a series of images into groups that are both spatially coherent and smooth along the time axis. We formulate segmentation as a Bayes...
Peter Orbanz, Samuel Braendle, Joachim M. Buhmann
ICANN
2010
Springer
13 years 8 months ago
Computational Properties of Probabilistic Neural Networks
We discuss the problem of overfitting of probabilistic neural networks in the framework of statistical pattern recognition. The probabilistic approach to neural networks provides a...
Jiri Grim, Jan Hora
UAI
1996
13 years 10 months ago
Bayesian Learning of Loglinear Models for Neural Connectivity
This paper presents a Bayesian approach to learning the connectivity structure of a group of neurons from data on configuration frequencies. A major objective of the research is t...
Kathryn B. Laskey, Laura Martignon
JMLR
2012
11 years 11 months ago
Graphlet decomposition of a weighted network
We introduce the graphlet decomposition of a weighted network, which encodes a notion of social information based on social structure. We develop a scalable algorithm, which combi...
Hossein Azari Soufiani, Edo Airoldi
FLAIRS
2001
13 years 10 months ago
Maximal Prime Subgraph Decomposition of Bayesian Networks
A maximal prime subgraph decomposition junction tree (MPD-JT) is a useful computational structure that facilitates lazy propagation in Bayesian networks (BNs). A graphical method ...
Kristian G. Olesen, Anders L. Madsen