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» Efficient Discovery of Confounders in Large Data Sets
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ICPR
2010
IEEE
15 years 4 months ago
Performance Evaluation of Automatic Feature Discovery Focused within Error Clusters
We report performance evaluation of our automatic feature discovery method on the publicly available Gisette dataset: a set of 29 features discovered by our method ranks 129 among...
Sui-Yu Wang, Henry S. Baird
BMCBI
2007
141views more  BMCBI 2007»
15 years 6 months ago
HeliCis: a DNA motif discovery tool for colocalized motif pairs with periodic spacing
Background: Correct temporal and spatial gene expression during metazoan development relies on combinatorial interactions between different transcription factors. As a consequence...
Erik Larsson, Per Lindahl, Petter Mostad
JMLR
2010
108views more  JMLR 2010»
15 years 28 days ago
Tree Decomposition for Large-Scale SVM Problems
To handle problems created by large data sets, we propose a method that uses a decision tree to decompose a given data space and train SVMs on the decomposed regions. Although the...
Fu Chang, Chien-Yang Guo, Xiao-Rong Lin, Chi-Jen L...
KDD
2004
ACM
112views Data Mining» more  KDD 2004»
16 years 6 months ago
A rank sum test method for informative gene discovery
Finding informative genes from microarray data is an important research problem in bioinformatics research and applications. Most of the existing methods rank features according t...
Lin Deng, Jian Pei, Jinwen Ma, Dik Lun Lee
ICDE
2007
IEEE
218views Database» more  ICDE 2007»
16 years 7 months ago
SKYPEER: Efficient Subspace Skyline Computation over Distributed Data
Skyline query processing has received considerable attention in the recent past. Mainly, the skyline query is used to find a set of non dominated data points in a multidimensional...
Akrivi Vlachou, Christos Doulkeridis, Yannis Kotid...