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» Scalable Data Mining with Model Constraints
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ICDM
2007
IEEE
129views Data Mining» more  ICDM 2007»
14 years 2 months ago
Semi-supervised Clustering Using Bayesian Regularization
Text clustering is most commonly treated as a fully automated task without user supervision. However, we can improve clustering performance using supervision in the form of pairwi...
Zuobing Xu, Ram Akella, Mike Ching, Renjie Tang
KDD
2009
ACM
191views Data Mining» more  KDD 2009»
14 years 8 months ago
Scalable pseudo-likelihood estimation in hybrid random fields
Learning probabilistic graphical models from high-dimensional datasets is a computationally challenging task. In many interesting applications, the domain dimensionality is such a...
Antonino Freno, Edmondo Trentin, Marco Gori
PVLDB
2010
146views more  PVLDB 2010»
13 years 2 months ago
HaLoop: Efficient Iterative Data Processing on Large Clusters
The growing demand for large-scale data mining and data analysis applications has led both industry and academia to design new types of highly scalable data-intensive computing pl...
Yingyi Bu, Bill Howe, Magdalena Balazinska, Michae...
SDM
2003
SIAM
129views Data Mining» more  SDM 2003»
13 years 9 months ago
Approximate Query Answering by Model Averaging
In earlier work we have introduced and explored a variety of different probabilistic models for the problem of answering selectivity queries posed to large sparse binary data set...
Dmitry Pavlov, Padhraic Smyth
CIKM
2000
Springer
14 years 1 days ago
Scalable association-based text classification
Naïve Bayes (NB) classifier has long been considered a core methodology in text classification mainly due to its simplicity and computational efficiency. There is an increasing n...
Dimitris Meretakis, Dimitris Fragoudis, Hongjun Lu...