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» Automorphic Decompositions of Graphs
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DM
2008
96views more  DM 2008»
15 years 3 months ago
Generating 3-vertex connected spanning subgraphs
In this paper we present an algorithm to generate all minimal 3-vertex connected spanning subgraphs of an undirected graph with n vertices and m edges in incremental polynomial tim...
Endre Boros, Konrad Borys, Vladimir Gurvich, G&aac...
171
Voted
AAAI
2010
15 years 4 months ago
Unsupervised Learning of Event Classes from Video
We present a method for unsupervised learning of event classes from videos in which multiple actions might occur simultaneously. It is assumed that all such activities are produce...
Muralikrishna Sridhar, Anthony G. Cohn, David C. H...
JMLR
2010
134views more  JMLR 2010»
14 years 10 months ago
Inference of Graphical Causal Models: Representing the Meaningful Information of Probability Distributions
This paper studies the feasibility and interpretation of learning the causal structure from observational data with the principles behind the Kolmogorov Minimal Sufficient Statist...
Jan Lemeire, Kris Steenhaut
132
Voted
AAAI
2011
14 years 3 months ago
Stopping Rules for Randomized Greedy Triangulation Schemes
Many algorithms for performing inference in graphical models have complexity that is exponential in the treewidth - a parameter of the underlying graph structure. Computing the (m...
Andrew Gelfand, Kalev Kask, Rina Dechter
130
Voted
AI
2006
Springer
15 years 7 months ago
Exploiting Dynamic Independence in a Static Conditioning Graph
Abstract. A conditioning graph (CG) is a graphical structure that attempt to minimize the implementation overhead of computing probabilities in belief networks. A conditioning grap...
Kevin Grant, Michael C. Horsch