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» Numbers in Multi-relational Data Mining
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KDD
2008
ACM
186views Data Mining» more  KDD 2008»
16 years 7 days ago
Cut-and-stitch: efficient parallel learning of linear dynamical systems on smps
Multi-core processors with ever increasing number of cores per chip are becoming prevalent in modern parallel computing. Our goal is to make use of the multi-core as well as multi...
Lei Li, Wenjie Fu, Fan Guo, Todd C. Mowry, Christo...
KDD
2007
ACM
156views Data Mining» more  KDD 2007»
16 years 7 days ago
Estimating rates of rare events at multiple resolutions
We consider the problem of estimating occurrence rates of rare events for extremely sparse data, using pre-existing hierarchies to perform inference at multiple resolutions. In pa...
Deepak Agarwal, Andrei Z. Broder, Deepayan Chakrab...
KDD
2003
ACM
129views Data Mining» more  KDD 2003»
16 years 7 days ago
Empirical comparisons of various voting methods in bagging
Finding effective methods for developing an ensemble of models has been an active research area of large-scale data mining in recent years. Models learned from data are often subj...
Kelvin T. Leung, Douglas Stott Parker Jr.
DATAMINE
1999
152views more  DATAMINE 1999»
14 years 11 months ago
Discovery of Frequent DATALOG Patterns
Discovery of frequent patterns has been studied in a variety of data mining settings. In its simplest form, known from association rule mining, the task is to discover all frequent...
Luc Dehaspe, Hannu Toivonen
PAKDD
2009
ACM
209views Data Mining» more  PAKDD 2009»
15 years 9 months ago
Approximate Spectral Clustering.
Spectral clustering refers to a flexible class of clustering procedures that can produce high-quality clusterings on small data sets but which has limited applicability to large-...
Christopher Leckie, James C. Bezdek, Kotagiri Rama...