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» Knowledge-Driven Learning and Discovery
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IMC
2007
ACM
13 years 10 months ago
Learning network structure from passive measurements
The ability to discover network organization, whether in the form of explicit topology reconstruction or as embeddings that approximate topological distance, is a valuable tool. T...
Brian Eriksson, Paul Barford, Robert Nowak, Mark C...
RAID
1999
Springer
14 years 22 days ago
Combining Knowledge Discovery and Knowledge Engineering to Build IDSs
We have been developing a data mining (i.e., knowledge discovery) framework, MADAM ID, for Mining Audit Data for Automated Models for Intrusion Detection [LSM98, LSM99b, LSM99a]. ...
Wenke Lee, Salvatore J. Stolfo
BMCBI
2010
146views more  BMCBI 2010»
13 years 8 months ago
Nonnegative principal component analysis for mass spectral serum profiles and biomarker discovery
Background: As a novel cancer diagnostic paradigm, mass spectroscopic serum proteomic pattern diagnostics was reported superior to the conventional serologic cancer biomarkers. Ho...
Henry Han
SIGMOD
2004
ACM
184views Database» more  SIGMOD 2004»
14 years 8 months ago
CORDS: Automatic Discovery of Correlations and Soft Functional Dependencies
The rich dependency structure found in the columns of real-world relational databases can be exploited to great advantage, but can also cause query optimizers--which usually assum...
Ihab F. Ilyas, Volker Markl, Peter J. Haas, Paul B...
CVPR
2006
IEEE
14 years 10 months ago
Escaping local minima through hierarchical model selection: Automatic object discovery, segmentation, and tracking in video
Recently, the generative modeling approach to video segmentation has been gaining popularity in the computer vision community. For example, the flexible sprites framework has been...
Nebojsa Jojic, John M. Winn, Larry Zitnick