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ICASSP
2011
IEEE
12 years 11 months ago
Variability regularization in large-margin classification
This paper introduces a novel regularization strategy to address the generalization issues for large-margin classifiers from the Empirical Risk Minimization (ERM) perspective. Fi...
Dwi Sianto Mansjur, Ted S. Wada, Biing-Hwang Juang
ML
2008
ACM
222views Machine Learning» more  ML 2008»
13 years 7 months ago
Boosted Bayesian network classifiers
The use of Bayesian networks for classification problems has received significant recent attention. Although computationally efficient, the standard maximum likelihood learning me...
Yushi Jing, Vladimir Pavlovic, James M. Rehg
TSE
2008
129views more  TSE 2008»
13 years 7 months ago
Classifying Software Changes: Clean or Buggy?
This paper introduces a new technique for predicting latent software bugs, called change classification. Change classification uses a machine learning classifier to determine wheth...
Sunghun Kim, E. James Whitehead Jr., Yi Zhang 0001
HIS
2004
13 years 9 months ago
Classification Ensembles for Shaft Test Data: Empirical Evaluation
: A-scans from ultrasonic testing of long shafts are complex signals. The discrimination of different types of echoes is of importance for non-destructive testing and equipment mai...
Kyungmi Lee, Vladimir Estivill-Castro
BMCBI
2008
220views more  BMCBI 2008»
13 years 8 months ago
Gene prediction in metagenomic fragments: A large scale machine learning approach
Background: Metagenomics is an approach to the characterization of microbial genomes via the direct isolation of genomic sequences from the environment without prior cultivation. ...
Katharina J. Hoff, Maike Tech, Thomas Lingner, Rol...