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» Classification by Discriminative Regularization
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BIOINFORMATICS
2005
109views more  BIOINFORMATICS 2005»
15 years 1 months ago
Prediction error estimation: a comparison of resampling methods
In genomic studies, thousands of features are collected on relatively few samples. One of the goals of these studies is to build classifiers to predict the outcome of future obser...
Annette M. Molinaro, Richard Simon, Ruth M. Pfeiff...
SIAMIS
2010
152views more  SIAMIS 2010»
14 years 8 months ago
Nonparametric Regression between General Riemannian Manifolds
We study nonparametric regression between Riemannian manifolds based on regularized empirical risk minimization. Regularization functionals for mappings between manifolds should re...
Florian Steinke, Matthias Hein, Bernhard Schö...
BMCBI
2008
164views more  BMCBI 2008»
15 years 1 months ago
Word correlation matrices for protein sequence analysis and remote homology detection
Background: Classification of protein sequences is a central problem in computational biology. Currently, among computational methods discriminative kernel-based approaches provid...
Thomas Lingner, Peter Meinicke
BMCBI
2011
14 years 5 months ago
To aggregate or not to aggregate high-dimensional classifiers
Background: High-throughput functional genomics technologies generate large amount of data with hundreds or thousands of measurements per sample. The number of sample is usually m...
Cheng-Jian Xu, Huub C. J. Hoefsloot, Age K. Smilde
CVPR
2003
IEEE
16 years 3 months ago
Kullback-Leibler Boosting
In this paper, we develop a general classification framework called Kullback-Leibler Boosting, or KLBoosting. KLBoosting has following properties. First, classification is based o...
Ce Liu, Heung-Yeung Shum