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» Learning from Highly Structured Data by Decomposition
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HICSS
2006
IEEE
115views Biometrics» more  HICSS 2006»
15 years 10 months ago
Learning about Interoperability for Emergency Response: Geographic Information Technologies and the World Trade Center Crisis
Geographic information technologies (GIT) have the potential to integrate information among multiple organizations. In fact, some of the most impressive advantages of using geo-sp...
Teresa M. Harrison, José Ramón Gil-G...
AMAI
2004
Springer
15 years 9 months ago
Using the Central Limit Theorem for Belief Network Learning
Learning the parameters (conditional and marginal probabilities) from a data set is a common method of building a belief network. Consider the situation where we have known graph s...
Ian Davidson, Minoo Aminian
WWW
2003
ACM
16 years 5 months ago
Piazza: data management infrastructure for semantic web applications
The Semantic Web envisions a World Wide Web in which data is described with rich semantics and applications can pose complex queries. To this point, researchers have defined new l...
Alon Y. Halevy, Zachary G. Ives, Peter Mork, Igor ...
VIIP
2001
15 years 5 months ago
Using Graphics Cards for Quantized FEM Computations
Graphics cards exercise increasingly more computing power and are highly optimized for high data transfer volumes. In contrast typical workstations perform badly when data exceeds...
Martin Rumpf, Robert Strzodka
MICS
2008
72views more  MICS 2008»
15 years 4 months ago
Dynamic Multi-level Overlay Graphs for Shortest Paths
Multi-level overlay graphs represent a speed-up technique for shortest paths computation which is based on a hierarchical decomposition of a weighted directed graph G. They have b...
Francesco Bruera, Serafino Cicerone, Gianlorenzo D...