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» Learning Instance-Specific Predictive Models
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MCS
2005
Springer
14 years 2 months ago
Ensembles of Classifiers from Spatially Disjoint Data
We describe an ensemble learning approach that accurately learns from data that has been partitioned according to the arbitrary spatial requirements of a large-scale simulation whe...
Robert E. Banfield, Lawrence O. Hall, Kevin W. Bow...
ICML
2007
IEEE
14 years 9 months ago
Simple, robust, scalable semi-supervised learning via expectation regularization
Although semi-supervised learning has been an active area of research, its use in deployed applications is still relatively rare because the methods are often difficult to impleme...
Gideon S. Mann, Andrew McCallum
BMCBI
2007
128views more  BMCBI 2007»
13 years 9 months ago
Combining classifiers to predict gene function in Arabidopsis thaliana using large-scale gene expression measurements
Background: Arabidopsis thaliana is the model species of current plant genomic research with a genome size of 125 Mb and approximately 28,000 genes. The function of half of these ...
Hui Lan, Rachel Carson, Nicholas J. Provart, Antho...
KDD
2012
ACM
205views Data Mining» more  KDD 2012»
11 years 11 months ago
Rank-loss support instance machines for MIML instance annotation
Multi-instance multi-label learning (MIML) is a framework for supervised classification where the objects to be classified are bags of instances associated with multiple labels....
Forrest Briggs, Xiaoli Z. Fern, Raviv Raich
BMCBI
2010
127views more  BMCBI 2010»
13 years 9 months ago
Computational prediction of type III secreted proteins from gram-negative bacteria
Background: Type III secretion system (T3SS) is a specialized protein delivery system in gramnegative bacteria that injects proteins (called effectors) directly into the eukaryoti...
Yang Yang, Jiayuan Zhao, Robyn L. Morgan, Wenbo Ma...