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» Efficient Discovery of Confounders in Large Data Sets
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INFOVIS
2003
IEEE
15 years 11 months ago
Interactive Hierarchical Dimension Ordering, Spacing and Filtering for Exploration of High Dimensional Datasets
Large numbers of dimensions not only cause clutter in multidimensional visualizations, but also make it difficult for users to navigate the data space. Effective dimension manage...
Jing Yang, Wei Peng, Matthew O. Ward, Elke A. Rund...
WSDM
2012
ACM
246views Data Mining» more  WSDM 2012»
14 years 1 months ago
Auralist: introducing serendipity into music recommendation
Recommendation systems exist to help users discover content in a large body of items. An ideal recommendation system should mimic the actions of a trusted friend or expert, produc...
Yuan Cao Zhang, Diarmuid Ó Séaghdha,...
ICML
2009
IEEE
16 years 7 months ago
Bayesian inference for Plackett-Luce ranking models
This paper gives an efficient Bayesian method for inferring the parameters of a PlackettLuce ranking model. Such models are parameterised distributions over rankings of a finite s...
John Guiver, Edward Snelson
BMCBI
2004
185views more  BMCBI 2004»
15 years 6 months ago
Linear fuzzy gene network models obtained from microarray data by exhaustive search
Background: Recent technological advances in high-throughput data collection allow for experimental study of increasingly complex systems on the scale of the whole cellular genome...
Bahrad A. Sokhansanj, J. Patrick Fitch, Judy N. Qu...
BMCBI
2002
188views more  BMCBI 2002»
15 years 6 months ago
The limit fold change model: A practical approach for selecting differentially expressed genes from microarray data
Background: The biomedical community is developing new methods of data analysis to more efficiently process the massive data sets produced by microarray experiments. Systematic an...
David M. Mutch, Alvin Berger, Robert Mansourian, A...