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» Learning from Highly Structured Data by Decomposition
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ICML
2005
IEEE
16 years 5 months ago
Ensembles of biased classifiers
We propose a novel ensemble learning algorithm called Triskel, which has two interesting features. First, Triskel learns an ensemble of classifiers, each biased to have high preci...
Andreas Heß, Nicholas Kushmerick, Rinat Khou...
134
Voted
BMCBI
2010
97views more  BMCBI 2010»
15 years 4 months ago
Biomarker discovery in heterogeneous tissue samples -taking the in-silico deconfounding approach
Background: For heterogeneous tissues, such as blood, measurements of gene expression are confounded by relative proportions of cell types involved. Conclusions have to rely on es...
Dirk Repsilber, Sabine Kern, Anna Telaar, Gerhard ...
154
Voted
WWW
2006
ACM
16 years 4 months ago
Compressing and searching XML data via two zips
XML is fast becoming the standard format to store, exchange and publish over the web, and is getting embedded in applications. Two challenges in handling XML are its size (the XML...
Paolo Ferragina, Fabrizio Luccio, Giovanni Manzini...
157
Voted
SPIRE
2010
Springer
15 years 2 months ago
Dual-Sorted Inverted Lists
Several IR tasks rely, to achieve high efficiency, on a single pervasive data structure called the inverted index. This is a mapping from the terms in a text collection to the docu...
Gonzalo Navarro, Simon J. Puglisi
TFS
2011
194views Education» more  TFS 2011»
14 years 11 months ago
Top-Down Induction of Fuzzy Pattern Trees
Fuzzy pattern tree induction was recently introduced as a novel machine learning method for classification. Roughly speaking, a pattern tree is a hierarchical, tree-like structur...
R. Senge, Eyke Hüllermeier