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» Informative sampling for large unbalanced data sets
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WSDM
2012
ACM
252views Data Mining» more  WSDM 2012»
12 years 3 months ago
WebSets: extracting sets of entities from the web using unsupervised information extraction
We describe a open-domain information extraction method for extracting concept-instance pairs from an HTML corpus. Most earlier approaches to this problem rely on combining cluste...
Bhavana Bharat Dalvi, William W. Cohen, Jamie Call...
SIGMOD
2004
ACM
144views Database» more  SIGMOD 2004»
14 years 7 months ago
Information-Theoretic Tools for Mining Database Structure from Large Data Sets
Periklis Andritsos, Renée J. Miller, Panayi...
CSDA
2008
65views more  CSDA 2008»
13 years 7 months ago
How to compare small multivariate samples using nonparametric tests
In plant pathology, in particular, and plant science, in general, experiments are often conducted to determine disease and related responses of plants to various treatments. Typic...
Arne C. Bathke, Solomon W. Harrar, Laurence V. Mad...
BMCBI
2008
186views more  BMCBI 2008»
13 years 7 months ago
Variable selection for large p small n regression models with incomplete data: Mapping QTL with epistases
Background: Identifying quantitative trait loci (QTL) for both additive and epistatic effects raises the statistical issue of selecting variables from a large number of candidates...
Min Zhang, Dabao Zhang, Martin T. Wells
ICRA
2010
IEEE
185views Robotics» more  ICRA 2010»
13 years 5 months ago
Heteroscedastic Gaussian processes for data fusion in large scale terrain modeling
This paper presents a novel approach to data fusion for stochastic processes that model spatial data. It addresses the problem of data fusion in the context of large scale terrain ...
Shrihari Vasudevan, Fabio T. Ramos, Eric Nettleton...