750 search results - page 73 / 150 » Reconstruction for Models on Random Graphs |
178
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KDD
2009
ACM
16 years 6 months ago
2009
ACM
Learning probabilistic graphical models from high-dimensional datasets is a computationally challenging task. In many interesting applications, the domain dimensionality is such a...
174
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ECML
2004
Springer
15 years 11 months ago
2004
Springer
This work presents a novel procedure for computing (1) distances between nodes of a weighted, undirected, graph, called the Euclidean Commute Time Distance (ECTD), and (2) a subspa...
165
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SODA
2007
ACM
15 years 7 months ago
2007
ACM
Random geometric graphs have been one of the fundamental models for reasoning about wireless networks: one places n points at random in a region of the plane (typically a square o...
171
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ICML
2010
IEEE
15 years 7 months ago
2010
IEEE
Learning temporal causal graph structures from multivariate time-series data reveals important dependency relationships between current observations and histories, and provides a ...
127
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JEI
2006
15 years 6 months ago
2006
We present our research efforts toward the deployment of 3-D sensing technology to an under-vehicle inspection robot. The 3-D sensing modality provides flexibility with ambient lig...