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» On the Boolean-Width of a Graph: Structure and Applications
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ICDM
2007
IEEE
175views Data Mining» more  ICDM 2007»
14 years 2 months ago
gApprox: Mining Frequent Approximate Patterns from a Massive Network
Recently, there arise a large number of graphs with massive sizes and complex structures in many new applications, such as biological networks, social networks, and the Web, deman...
Chen Chen, Xifeng Yan, Feida Zhu, Jiawei Han
CIKM
2010
Springer
13 years 5 months ago
Regularization and feature selection for networked features
In the standard formalization of supervised learning problems, a datum is represented as a vector of features without prior knowledge about relationships among features. However, ...
Hongliang Fei, Brian Quanz, Jun Huan
UAI
2007
13 years 9 months ago
"I Can Name that Bayesian Network in Two Matrixes!"
The traditional approach to building Bayesian networks is to build the graphical structure using a graphical editor and then add probabilities using a separate spreadsheet for eac...
Russell Almond
ASPLOS
2011
ACM
12 years 11 months ago
NV-Heaps: making persistent objects fast and safe with next-generation, non-volatile memories
nt, user-defined objects present an attractive abstraction for working with non-volatile program state. However, the slow speed of persistent storage (i.e., disk) has restricted ...
Joel Coburn, Adrian M. Caulfield, Ameen Akel, Laur...
DLOG
2004
13 years 9 months ago
Towards Explaining Semantic Matching
Interoperability among systems using different term vocabularies requires mappings between them. Matching applications generate these mappings. When the matching process utilizes ...
Deborah L. McGuinness, Pavel Shvaiko, Fausto Giunc...