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ECCV
2010
Springer
15 years 7 months ago
MIForests: Multiple-Instance Learning with Randomized Trees
Abstract. Multiple-instance learning (MIL) allows for training classifiers from ambiguously labeled data. In computer vision, this learning paradigm has been recently used in many ...
Christian Leistner, Amir Saffari, Horst Bischof
BIBE
2008
IEEE
160views Bioinformatics» more  BIBE 2008»
16 years 1 months ago
Parallel integration of heterogeneous genome-wide data sources
— Heterogeneous genome-wide data sources capture information on various aspects of complex biological systems. For instance, transcriptome, interactome and phenome-level informat...
Derek Greene, Kenneth Bryan, Padraig Cunningham
HPCN
1998
Springer
15 years 11 months ago
PARAFLOW: A Dataflow Distributed Data-Computing System
We describe the Paraflow system for connecting heterogeneous computing services together into a flexible and efficient data-mining metacomputer. There are three levels of parallel...
Roy Williams, Bruce Sears
BMCBI
2008
219views more  BMCBI 2008»
15 years 7 months ago
Classification of premalignant pancreatic cancer mass-spectrometry data using decision tree ensembles
Background: Pancreatic cancer is the fourth leading cause of cancer death in the United States. Consequently, identification of clinically relevant biomarkers for the early detect...
Guangtao Ge, G. William Wong
182
Voted
BMCBI
2006
142views more  BMCBI 2006»
15 years 6 months ago
Improving the Performance of SVM-RFE to Select Genes in Microarray Data
Background: Recursive Feature Elimination is a common and well-studied method for reducing the number of attributes used for further analysis or development of prediction models. ...
Yuanyuan Ding, Dawn Wilkins