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» Algorithms for subsequence combinatorics
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KDD
2008
ACM
138views Data Mining» more  KDD 2008»
16 years 4 months ago
Quantitative evaluation of approximate frequent pattern mining algorithms
Traditional association mining algorithms use a strict definition of support that requires every item in a frequent itemset to occur in each supporting transaction. In real-life d...
Rohit Gupta, Gang Fang, Blayne Field, Michael Stei...
3DIM
2007
IEEE
15 years 10 months ago
Cached k-d tree search for ICP algorithms
The ICP (Iterative Closest Point) algorithm is the de facto standard for geometric alignment of threedimensional models when an initial relative pose estimate is available. The ba...
Andreas Nüchter, Kai Lingemann, Joachim Hertz...
CIKM
2001
Springer
15 years 8 months ago
Sliding-Window Filtering: An Efficient Algorithm for Incremental Mining
We explore in this paper an effective sliding-window filtering (abbreviatedly as SWF) algorithm for incremental mining of association rules. In essence, by partitioning a transact...
Chang-Hung Lee, Cheng-Ru Lin, Ming-Syan Chen
BMCBI
2006
119views more  BMCBI 2006»
15 years 4 months ago
Utilization of two sample t-test statistics from redundant probe sets to evaluate different probe set algorithms in GeneChip stu
Background: The choice of probe set algorithms for expression summary in a GeneChip study has a great impact on subsequent gene expression data analysis. Spiked-in cRNAs with know...
Zihua Hu, Gail R. Willsky
JMLR
2010
134views more  JMLR 2010»
14 years 11 months ago
Bayesian Algorithms for Causal Data Mining
We present two Bayesian algorithms CD-B and CD-H for discovering unconfounded cause and effect relationships from observational data without assuming causal sufficiency which prec...
Subramani Mani, Constantin F. Aliferis, Alexander ...