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BMCBI
2011
12 years 8 months ago
A Beta-Mixture Model for Dimensionality Reduction, Sample Classification and Analysis
Background: Patterns of genome-wide methylation vary between tissue types. For example, cancer tissue shows markedly different patterns from those of normal tissue. In this paper ...
Kirsti Laurila, Bodil Oster, Claus L. Andersen, Ph...
ECCV
2006
Springer
14 years 6 months ago
Sampling Representative Examples for Dimensionality Reduction and Recognition - Bootstrap Bumping LDA
Abstract. We present a novel method for dimensionality reduction and recognition based on Linear Discriminant Analysis (LDA), which specifically deals with the Small Sample Size (S...
Hui Gao, James W. Davis
SIAMSC
2008
198views more  SIAMSC 2008»
13 years 4 months ago
Model Reduction for Large-Scale Systems with High-Dimensional Parametric Input Space
A model-constrained adaptive sampling methodology is proposed for reduction of large-scale systems with high-dimensional parametric input spaces. Our model reduction method uses a ...
T. Bui-Thanh, Karen Willcox, Omar Ghattas
ICIP
2006
IEEE
14 years 6 months ago
Joint Dimensionality Reduction, Classification and Segmentation of Hyperspectral Images
Dimensionality reduction, spectral classification and segmentation are the three main problems in hyperspectral image analysis. In this paper we propose a Bayesian estimation appr...
Nadia Bali, Ali Mohammad-Djafari, Adel Mohammadpou...
BMCBI
2010
122views more  BMCBI 2010»
13 years 4 months ago
Ovarian cancer classification based on dimensionality reduction for SELDI-TOF data
Background: Recent advances in proteomics technologies such as SELDI-TOF mass spectrometry has shown promise in the detection of early stage cancers. However, dimensionality reduc...
Kai-Lin Tang, Tong-Hua Li, Wen-Wei Xiong, Kai Chen